Download Full Introduction to functional data analysis 1st edition piotr kokoszka PDF All Chapters

Page 1


Introduction to Functional Data Analysis 1st Edition Piotr Kokoszka

Visit to download the full and correct content document: https://textbookfull.com/product/introduction-to-functional-data-analysis-1st-edition-pio tr-kokoszka/

More products digital (pdf, epub, mobi) instant download maybe you interests ...

Introduction to Statistics and Data Analysis Roxy Peck

https://textbookfull.com/product/introduction-to-statistics-anddata-analysis-roxy-peck/

Introduction to error analysis the science of measurements uncertainties and data analysis Merrin

https://textbookfull.com/product/introduction-to-error-analysisthe-science-of-measurements-uncertainties-and-data-analysismerrin/

Introduction to Data Science Data Analysis and Prediction Algorithms with R 1st Edition By Rafael A. Irizarry

https://textbookfull.com/product/introduction-to-data-sciencedata-analysis-and-prediction-algorithms-with-r-1st-edition-byrafael-a-irizarry/

Functional Analysis: An Introduction to Metric Spaces, Hilbert Spaces, and Banach Algebras: Second Edition Joseph Muscat

https://textbookfull.com/product/functional-analysis-anintroduction-to-metric-spaces-hilbert-spaces-and-banach-algebrassecond-edition-joseph-muscat/

An Introduction to Secondary Data Analysis with IBM SPSS Statistics 1st Edition John Macinnes

https://textbookfull.com/product/an-introduction-to-secondarydata-analysis-with-ibm-spss-statistics-1st-edition-john-macinnes/

An Introduction to Statistical Methods and Data Analysis 7th Edition R. Lyman Ott

https://textbookfull.com/product/an-introduction-to-statisticalmethods-and-data-analysis-7th-edition-r-lyman-ott/

An Introduction to Secondary Data Analysis with IBM SPSS Statistics First Edition Macinnes

https://textbookfull.com/product/an-introduction-to-secondarydata-analysis-with-ibm-spss-statistics-first-edition-macinnes/

Granular Relational Data Mining How to Mine Relational Data in the Paradigm of Granular Computing 1st Edition Piotr Ho■ko (Auth.)

https://textbookfull.com/product/granular-relational-data-mininghow-to-mine-relational-data-in-the-paradigm-of-granularcomputing-1st-edition-piotr-honko-auth/

An Introduction to Resting State fMRI Functional Connectivity 1st Edition Janine Bijsterbosch

https://textbookfull.com/product/an-introduction-to-restingstate-fmri-functional-connectivity-1st-edition-janinebijsterbosch/

Introduction to Functional Data Analysis

CHAPMAN & HALL/CRC

Texts in Statistical Science Series

Series Editors

Francesca Dominici, Harvard School of Public Health, USA

Julian J. Faraway, University of Bath, UK

Martin Tanner, Northwestern University, USA

Jim Zidek, University of British Columbia, Canada

Statistical Theory: A Concise Introduction

F. Abramovich and Y. Ritov

Practical Multivariate Analysis, Fifth Edition

A. Afifi, S. May, and V.A. Clark

Practical Statistics for Medical Research

D.G. Altman

Interpreting Data: A First Course in Statistics

A.J.B. Anderson

Introduction to Probability with R

K. Baclawski

Linear Algebra and Matrix Analysis for Statistics

S. Banerjee and A. Roy

Modern Data Science with R

B. S. Baumer, D. T. Kaplan, and N. J. Horton

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition

P. J. Bickel and K. A. Doksum

Mathematical Statistics: Basic Ideas and Selected Topics, Volume II

P. J. Bickel and K. A. Doksum

Analysis of Categorical Data with R

C. R. Bilder and T. M. Loughin

Statistical Methods for SPC and TQM

D. Bissell

Introduction to Probability

J. K. Blitzstein and J. Hwang

Bayesian Methods for Data Analysis, Third Edition

B.P. Carlin and T.A. Louis

Second Edition

R. Caulcutt

The Analysis of Time Series: An Introduction, Sixth Edition

C. Chatfield

Introduction to Multivariate Analysis

C. Chatfield and A.J. Collins

Problem Solving: A Statistician’s Guide, Second Edition

C. Chatfield

Statistics for Technology: A Course in Applied Statistics, Third Edition

C. Chatfield

Analysis of Variance, Design, and Regression : Linear Modeling for Unbalanced Data, Second Edition

R. Christensen

Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians

R. Christensen, W. Johnson, A. Branscum, and T.E. Hanson

Modelling Binary Data, Second Edition

D. Collett

Modelling Survival Data in Medical Research, Third Edition

D. Collett

Introduction to Statistical Methods for Clinical Trials

T.D. Cook and D.L. DeMets

Applied Statistics: Principles and Examples

D.R. Cox and E.J. Snell

Multivariate Survival Analysis and Competing Risks

M. Crowder

Statistical Analysis of Reliability Data

M.J. Crowder, A.C. Kimber, T.J. Sweeting, and R.L. Smith

An Introduction to Generalized Linear Models, Third Edition

A.J. Dobson and A.G. Barnett

Nonlinear Time Series: Theory, Methods, and Applications with R Examples

R. Douc, E. Moulines, and D.S. Stoffer

Introduction to Optimization Methods and Their Applications in Statistics

B.S. Everitt

Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition

J.J. Faraway

Linear Models with R, Second Edition

J.J. Faraway

A Course in Large Sample Theory

T.S. Ferguson

Multivariate Statistics: A Practical Approach

B. Flury and H. Riedwyl

Readings in Decision Analysis

S. French

Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data

M. Friendly and D. Meyer

Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition

D. Gamerman and H.F. Lopes

Bayesian Data Analysis, Third Edition

A. Gelman, J.B. Carlin, H.S. Stern, D.B. Dunson, A. Vehtari, and D.B. Rubin

Multivariate Analysis of Variance and Repeated Measures: A Practical Approach for Behavioural Scientists

D.J. Hand and C.C. Taylor

Practical Longitudinal Data Analysis

D.J. Hand and M. Crowder

Logistic Regression Models

J.M. Hilbe

Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects

J.S. Hodges

Statistics for Epidemiology

N.P. Jewell

Stochastic Processes: An Introduction, Second Edition

P.W. Jones and P. Smith

The Theory of Linear Models

B. Jørgensen

Pragmatics of Uncertainty

J.B. Kadane

Principles of Uncertainty

J.B. Kadane

Graphics for Statistics and Data Analysis with R K.J. Keen

Mathematical Statistics

K. Knight

Introduction to Functional Data Analysis

P. Kokoszka and M. Reimherr

Introduction to Multivariate Analysis: Linear and Nonlinear Modeling

S. Konishi

Nonparametric Methods in Statistics with SAS Applications

O. Korosteleva

Modeling and Analysis of Stochastic Systems, Second Edition

V.G. Kulkarni

Exercises and Solutions in Biostatistical Theory

L.L. Kupper, B.H. Neelon, and S.M. O’Brien

Exercises and Solutions in Statistical Theory

L.L. Kupper, B.H. Neelon, and S.M. O’Brien

Design and Analysis of Experiments with R

J. Lawson

Design and Analysis of Experiments with SAS

J. Lawson

A Course in Categorical Data Analysis

T. Leonard

Statistics for Accountants

S. Letchford

Introduction to the Theory of Statistical Inference

H. Liero and S. Zwanzig

Statistical Theory, Fourth Edition

B.W. Lindgren

Stationary Stochastic Processes: Theory and Applications

G. Lindgren

Statistics for Finance

E. Lindström, H. Madsen, and J. N. Nielsen

The BUGS Book: A Practical Introduction to Bayesian Analysis

D. Lunn, C. Jackson, N. Best, A. Thomas, and D. Spiegelhalter

Introduction to General and Generalized Linear Models

H. Madsen and P. Thyregod

Time Series Analysis

H. Madsen

Pólya Urn Models

H. Mahmoud

Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition

B.F.J. Manly

Introduction to Randomized Controlled Clinical Trials, Second Edition

J.N.S. Matthews

Statistical Rethinking: A Bayesian Course with Examples in R and Stan

R. McElreath

Statistical Methods in Agriculture and Experimental Biology, Second Edition

R. Mead, R.N. Curnow, and A.M. Hasted

Statistics in Engineering: A Practical Approach

A.V. Metcalfe

Statistical Inference: An Integrated Approach, Second Edition

H. S. Migon, D. Gamerman, and F. Louzada

Beyond ANOVA: Basics of Applied Statistics

R.G. Miller, Jr.

A Primer on Linear Models

J.F. Monahan

Stochastic Processes: From Applications to Theory

P.D Moral and S. Penev

Applied Stochastic Modelling, Second Edition

B.J.T. Morgan

Elements of Simulation

B.J.T. Morgan

Probability: Methods and Measurement

A. O’Hagan

Introduction to Statistical Limit Theory

A.M. Polansky

Applied Bayesian Forecasting and Time Series

Analysis

A. Pole, M. West, and J. Harrison

Statistics in Research and Development, Time Series: Modeling, Computation, and Inference

R. Prado and M. West

Essentials of Probability Theory for Statisticians

M.A. Proschan and P.A. Shaw

Introduction to Statistical Process Control

P. Qiu

Sampling Methodologies with Applications

P.S.R.S. Rao

A First Course in Linear Model Theory

N. Ravishanker and D.K. Dey

Essential Statistics, Fourth Edition

D.A.G. Rees

Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists

F.J. Samaniego

Statistical Methods for Spatial Data Analysis

O. Schabenberger and C.A. Gotway

Bayesian Networks: With Examples in R

M. Scutari and J.-B. Denis

Large Sample Methods in Statistics

P.K. Sen and J. da Motta Singer

Spatio-Temporal Methods in Environmental Epidemiology

G. Shaddick and J.V. Zidek

Decision Analysis: A Bayesian Approach

J.Q. Smith

Analysis of Failure and Survival Data

P. J. Smith

Applied Statistics: Handbook of GENSTAT Analyses

E.J. Snell and H. Simpson

Applied Nonparametric Statistical Methods, Fourth Edition

P. Sprent and N.C. Smeeton

Data Driven Statistical Methods

P. Sprent

Generalized Linear Mixed Models: Modern Concepts, Methods and Applications

W. W. Stroup

Survival Analysis Using S: Analysis of Time-to-Event Data

M. Tableman and J.S. Kim

Applied Categorical and Count Data Analysis

W. Tang, H. He, and X.M. Tu

Elementary Applications of Probability Theory, Second Edition

H.C. Tuckwell

Introduction to Statistical Inference and Its Applications with R

M.W. Trosset

Understanding Advanced Statistical Methods

P.H. Westfall and K.S.S. Henning

Statistical Process Control: Theory and Practice, Third Edition

G.B. Wetherill and D.W. Brown

Generalized Additive Models: An Introduction with R S. Wood

Epidemiology: Study Design and Data Analysis, Third Edition M. Woodward

Practical Data Analysis for Designed Experiments

B.S. Yandell

Texts in Statistical Science

Introduction to Functional Data Analysis

Piotr Kokoszka

Colorado State University

Ft. Collins, Colorado

The Pennsylvania State University

University Park, Pennsylvania

CRC Press

Taylor & Francis Group

6000 Broken Sound Parkway NW, Suite 300

Boca Raton, FL 33487-2742

© 2017 by Taylor & Francis Group, LLC

CRC Press is an imprint of Taylor & Francis Group, an Informa business

No claim to original U.S. Government works

Printed on acid-free paper

Version Date: 20170315

International Standard Book Number-13: 978-1-498-74634-2 (Hardback)

This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint.

Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers.

For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged.

Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe.

Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com

and the CRC Press Web site at http://www.crcpress.com

ToZsuzsannaandWilliam,Elliott,andAlice Matthew

ToGudrunandVanessa Piotr

1Firststepsintheanalysisoffunctionaldata

2FurthertopicsinexploratoryFDA

5.1Leastsquaresestimationandapplicationtoangularmotion.

5.6Testofnoeffect.........................

6Functionalgeneralizedlinearmodels

6.2Scalar-on-functionGLM’s....................

6.3FunctionalresponseGLM....................

7.5Sparsefunctionalregression...................

7.6Chapter7problems.......................

8Functionaltimeseries

8.1Fundamentalconceptsoftimeseriesanalysis.........

8.6Testingstationarityoffunctionaltimeseries.........

8.7GenerationandestimationoftheFAR(1)modelusingpackage

8.8ConditionsfortheexistenceoftheFAR(1)process......

8.9Furtherreadingandothertopics................

8.10Chapter8problems.......................

9.1Fundamentalconceptsofspatialstatistics...........

9.4Meanfunctionestimation....................

9.5Implementationinthe R package

9.6Othertopicsandfurtherreading................

9.7Chapter9problems.......................

10ElementsofHilbertspacetheory

12Inferencefromarandomsample

Preface

Audienceandscope

Thisbookprovidesaconciseintroductiontothefieldoffunctionaldataanalysis(FDA).ItcanbeusedasatextbookforasemesterlongcourseonFDAfor advancedundergraduateorMSstatisticsmajors,aswellasforMSandPhD studentsinotherdisciplines,includingappliedmathematics,environmental science,publichealth,medicalresearch,geophysicalsciences,andeconomics. Itcanalsobeusedforself–studyandasareferenceforresearchersinthose fieldswhowishtoacquireasolidunderstandingofFDAmethodologyand practicalguidanceforitsimplementation.Eachchaptercontainsproblems andplentifulexamplesofrelevant R code.

ThefieldofFDAhasseenrapiddevelopmentoverthelasttwodecades.At present,FDAcanbeseenasasubfieldofstatisticsthathasreachedacertain maturitywithitscentralideasandmethodscrystalizedandgenerallyviewed asfundamentaltothesubject.Atthesametime,itsmethodshavebeenappliedtoquitebroadlyinmedicine,science,business,andengineering.While newtheoreticalandmethodologicaldevelopments,andnewapplications,are stillbeingreportedatafairrate,anintroductoryaccountwillbeusefulto studentsandresearchersseekinganaccessibleandsufficientlycomprehensive introductiontothesubject.SeveralFDAmonographsexist,buttheyareeitherolderorcoververyspecifictopics,andnoneofthemiswritteninthe styleofatextbook,withproblemsthatcanbeassignedashomeworkorused aspartofexaminations.Ourobjectiveistofurnishatextbookthatprovides anaccessibleintroductiontothefieldratherthanamonographthatexplores cuttingedgedevelopments.Thebookassumesasolidbackgroundincalculus,linearalgebra,distributionalprobabilitytheory,foundationsofstatistical inference,andsomefamiliaritywith R programming.Suchabackgroundis acquiredbyUSseniorandMSstudentsmajoringinstatisticsormathematics withastatisticsemphasis,andbyEuropeanthirdyearstudentswithsimilar specializations.Wedonotassumebackgroundinnonparametricstatisticsor advancedregressionmethods.Therequiredconceptsareexplainedinscalar settingsbeforetherelatedfunctionalconceptsaredeveloped.Referencesto moreadvancedresearchareprovidedforthosewhowishtogainamoreindepthunderstandingofaspecifictopic.Eachchapterendswithproblems thatfallintotwocategories:1)theoreticalproblems,mostlysimpleexercisesintendedtosolidifydefinitionsandconcepts,2) R baseddataanalytic problems.

ThereareanumberofverygoodbooksonFDA.Thebestknownisthe monographofRamsayandSilverman(2005),whichisthesecondeditionof abookoriginallypublishedin1997.Thefirsteditionislargelycreditedwith solidifyingFDAasanofficialsubbranchofstatistics.Theirworkprovidesa moredetailedtreatmentofmanytopicsonlyhighlightedinourbook,including

xv computationalaspectsofsmoothing,smoothingunderpositivityandmonotonicityconstraints,variousspecialcasesofthefunctionallinearmodel,and thedynamicalsystemsapproachtoFDA.Thecompanionbook,Ramsayand Silverman(2002),presentsamoredetailedanalysesofseveraldatasets.Anothercompanionbook,Ramsay etal. (2009)explainshowthemethodologyof RamsayandSilverman(2005)isimplementedinthe R package fda.Almost twentyyearshavepassedsincethepublicationofthemonographofRamsay andSilverman(2005)inwhichtherehavebeenseveralnotabledevelopments thatdeserveaplaceinatextbookexposition.Theseincludemethodologyfor sparselyobservedfunctionsandgeneralizedlinearmodelstogetherwiththeir R implementations,aswellasmethodologyfordependentfunctionaldataand itsimplementationinseveralrecentlydeveloped R packages.WhileRamsay andSilverman(2005)focusonmethodology,thebookofHsingandEubank (2015)containsarigorousandcomprehensiveexpositionoftheHilbertspace frameworkforfunctionaldata.Functionallineartimeseriesmodelswithinan evenmoregeneralBanachspaceframeworkarestudiedinBosq(2000).Our bookcontainsseveralchaptersthatpresentthemostfundamentalresultsof Hilbertspacetheoryforfunctionaldata.ThebookofFerratyandVieu(2006) presentsmathematicaltheorybehindnonlinearfunctionalregression,atopic whichisonlybrieflymentionedinourbook.ShiandChoi(2011)developa BayesianGaussianprocessframeworkforfunctionalregression.Thebookof Horv´athandKokoszka(2012)presentsageneralintroductiontothemathematicalFDAframeworkandthenbranchesintoseveraldirectionswiththe mostnovelexpositionpertainingtofunctionaldatawhichexhibitdependence overtimeorspace.ThemathematicallevelofHorv´athandKokoszka(2012) issignificantlyhigherthanofthisbook.ThecollectionsFerratyandRomain (2011)andFerraty(2011)containcontributionsbyleadingresearchersinthe fieldwhichsummarizeanumberofrecentdevelopmentsinFDAandpoint towardsfutureresearchdirections.

Outlineofthecontents

Thebookconsistsof12chaptersthatcanbedividedintoseveralgroups. Chapters1 and 2 introducethemostfundamentalconceptsofFDAincluding basisexpansions,meanandcovariancefunctions,functionalprincipalcomponentsandpenalizedsmoothing. Chapter3 givesanintroductiontothe Hilbertspaceframeworkformodelingandinferenceoffunctionaldata.This ischapterisdesignedtobeverybroadlyaccessible,focusingonmathematical concepts.Theobjectiveistoprovidethereaderwithsufficientbackgroundto understandthemathematicalconceptsandformulationsusedinsubsequent chapters.Thoseinterestedinamoremathematicallyrigorousfoundationcan replace Chapter3 with Chapters10 and 11. Chapters4, 5,and 6 focuson functionalregressionmodels. Chapter4 isconcernedwithscalar–on–function regression.Inthissimplest,butperhapsmostimportant,setting,wediscuss thedifferencesbetweenthefunctionalandtraditionalregression,andexplain

howdifficultiesandadvantagesspecifictofunctionalsettingsareaddressed.In Chapter5, weturntoregressionmodelswithfunctionalresponses. Chapter6 isdedicatedtoafunctionalversionofgeneralizedlinearmodels,whichhas foundmanyapplicationsinmedicalandbiologyresearch. Chapter7 provides anintroductiontotheanalysisofsparselyobservedfunctions.Suchdataarise ofteninlongitudinalmedicalstudieswhereasmallnumberofmeasurements, oftencharacterizedbyanonnegligibleobservationerror,areavailableforeach subject. Chapters8 and 9 introducedependentfunctionaldatastructures, fortimeseriesandspatialdata,respectively. Chapters10 and 11 providea self–containedandrigorousintroductiontothemathematicaltheoryunderlyingFDA.Generally,onlyreferencestocomplexproofsaregiven,butthe expositionisrigorousandcanserveasastartingpointforfurtheradvanced research.Weconcludewith Chapter12 whichintroducesmoreadvancedinferentialtoolsforfunctionaldata,focusingonhypothesistestingandconfidence bands.If Chapters10 and 11 areusedasasubstitutionfor Chapter3, then thischaptercanfollowimmediatelyafter.

Chapters6, 7, 8, 9,and 12 introducerelativelyrecentresearch,whichhas notyetbeenpresentedelsewhereinasystematictextbookexposition.There areimportant,dynamicallydevelopingareasofFDAwhicharenotincluded inthistextbook.Theseincludeclassificationandclustering,theinterfacebetweenfunctionaldataanddifferentialequations,andfunctionaldatadefined onmanifolds.Somereferencesaregivenin Section2.4.

Acknowledgements

JohnKimmelprovidedusefuleditorialguidanceduringthepreparationofthis book.Thereviewsheobtainedhelpedusreshapeandenhancethebookat severalstagesofpreparation;wethanktheanonymousreviewers.Severalresearchersprovidedsubstantivehelpinthepreparationofthisbook.Sections thatcontain R codeareoftenbasedonthecodeprovidedbyresearchersinvolvedinthepreparationofthespecificpackages.JeffGoldsmithprovidedthe codepresentedin Section4.7,PhilReissandFabianScheiplin Section5.4, andGilesHookerin Section5.5.FabianScheiplalsocontributedtothecode in Section6.4.Thefinalversionofthecodepresentedin Chapter8 waspreparedbyHanLinShang,withcontributionsfromAlexanderAue,Siegfried H¨ormannandGregoryRice.RobertasGabryspreparedthecodepresentedin Section8.7.PedroDelicadowrotethecodeshownin Chapter9 andhelped usimproveothersectionsofthatchapter.Someproblemsweresuggestedby PhDstudentsatColoradoStateUniversity:CodyAlsaker,RanFu,Aaron NielsenandZachWeller.HyunphilChoi,JohannesKlepsch,NedaMohammadiJouzdani,StathisPaparoditis,andBenZhengfoundmanytyposand recommendedimprovementstotheexposition.Wethankthemallfortheir kindhelp.WeacknowledgegeneroussupportfromtheUnitedStatesNational ScienceFoundationandtheNationalSecurityAgency.

PiotrKokoszkaandMatthewReimherr

Firststepsintheanalysisoffunctional data

Functionaldataanalysis,FDA,hasexpandedrapidlyintheyearsleading uptothistext.Thewidebreadthofapplicationsandtoolsmakeaprecise definitionofFDAsomewhatdifficult.Atahighlevel,oneshouldthinkof FDAasarisingwhenoneofthevariablesorunitsofinterestinadataset canbenaturallyviewedasasmoothcurveorfunction.FDAcanthenbe thoughtofasthestatisticalanalysisofsamplesofcurves(possiblycombined withvectorsorscalarsaswell).

Thischapterservesthedualpurposeofintroducingbasicconceptsand discussingthemostimportant R functionsformanipulatingfunctionaldata. Ramsay etal. (2009)provideamuchmorecomprehensiveanddetaileddescriptionofthe R andMATLABtoolsusedforanalysisoffunctionaldata. Ourobjectiveistoenablethereadertoperformsimpleanalysesin R andgain someworkingunderstandingofFDA.Thescopeofthischapteristherefore limited,manymoredevelopmentswillbepresentedinthefollowingchapters. Inparticular,werestrictourselvestotheanalysisofrandomsamplesofdensely observedcurves.ThemonographofRamsayandSilverman(2005)elaborates onmanytopicstoucheduponinthischapter;furtherdetailedexamplesare presentedinRamsayandSilverman(2002).

ThesimplestdatasetencounteredinFDAisasampleoftheform xn(tj,n) R,tj,n [T1,T2],n =1, 2,...,N,j =1,...,Jn. (1.1)

Bythiswemeanthat N curvesareobservedonacommoninterval[T1,T2]. Thevaluesofthecurvesareneverknownatallpoints t [T1,T2],theyare availableonlyatsomespecificpoints tj,n whichcanbedifferentfordifferent curves xn.ManyimportantapplicationsofFDAdealwithsituationswhere thenumberofpoints, tj,n ,percurveissmall,forexampleasingledigit number.Suchcasesrequirecustommethodologywhichwillbepresentedin Chapter7.Inthischapter,wefocusonsituationswherethenumberofpoints percurveislarge.Ineithercase,afundamentalideaofFDAisthattheobjects wewishtostudyaresmoothcurves

xn(t): t [T1,T2],n =1, 2,...,N , (1.2)

forwhichthevalues xn(t)existatanypoint t,butareobservedonlyatselected points tj,n.Forexample,inamedicaltreatment,onemaybeinterestedinthe

FIGURE1.1:Thehorizontalcomponentofthemagneticfieldmeasuredat Honolulumagneticobservatoryfrom1/1/200100:00UTto1/7/200124:00 UT.Theverticaldashedlinesseparate24hdays.Eachdailycurveisviewed asasinglefunctionalobservation.

concentration xn(t)ofacertainproteininthebloodofpatient n attime t Thenumber xn(t)existsatanytime t,butitsvalueismeasuredonlyatthose timeswhenthepatientsbloodistested,possiblytwiceayear.Functionaldata forwhichonlyafewobservationsareavailableforeverycurvearereferredto as sparse.Attheotherendofthespectrum,wemayconsiderthestrength, xn(t),ofthemagneticfieldmeasuredatsomelocation,forexampleatthe Honolulumagneticobservatory,attime t onday n,see Figure1.1. Again, xn(t)existsatanytime,butitsvalueisavailableonlyatspecifictimes.Inthis case,adigitalmagnetometerrecordsthevalueseveryfiveseconds,resulting in17,280observationsperday.Suchfunctionaldataarereferredtoas densely observed.Ofcourse,thereisnoobviouscutoffpointbetweensparselyand denselyobservedcurves,andtherearemanysituationswhicharedifficult toclassifyinthisway.Stillanotherinterestingexampleisprovidedbyhigh frequencyfinancialdata. Figure1.2 showsthevaluesofMicrosoftstockminute byminute.Infact,sharesoflargecompaniesaretradeduptoathousandtimes everysecond,sosuchfunctionscanbeverydenselyobserved.Conceptually, itisnotclearifthepriceexistsbetweentrades,buttheusualmathematical frameworkforpricedatausescontinuoustimestochasticdifferentialequations, sothepricefunctionisdefinedforevery t

FIGURE1.2:Microsoftstockpricesinone-minuteresolution,May1-5,8-12, 2006.Theclosingpriceonday n isnotthesameastheopeningpriceon day n +1.Thedisplayeddatacanbeviewedasasampleof10functional observations.

AmajorfocusinFDAistheshapeoftheobservedfunctionsoroffunctions whichsummarizethepropertiesofthedatainsomespecificway.Forexample, itmaybeofinteresthowacertaintreatmentaffectsthemeanproteinlevelof patients.Onewouldbeinterestedinconstructingacurvewhichdescribeshow thislevelchangesovertimeinagroupofpatients.Formagnetometerdata, spacephysicsresearchersarenotinterestedinthevalueofthefieldeveryfive seconds,butintheshapeofthecurveoverseveraldays.Theshapesofsuch curvesatmanylocationsallowresearcherstomakeinferencesaboutphysical processesoccurringinnearEarthspacewherenoinstrumentsareplaced.

1.1Basisexpansions

Typically,thefirststepinworkingwithfunctionaldataoftheform(1.1)is toexpressthembymeansofa basisexpansion

In(1.3),the Bm aresomestandardcollectionof basisfunctions,likesplines wavelets,orsineandcosinefunctions;wewilldiscusstheminthefollowing. Expansion(1.3)reflectstheintuitionthatthedata(1.1)areobservationsfrom

FIGURE1.3:PlotsofthefirstfiveB–splines(left)andFourier(right)basis functions.

smoothfunctionsthatsharesomeshapeproperties,andsocanbeapproximatedaslinearcombinationsofsome M basicshapes Bm,with M being typicallysmallerthanthenumberofobservedtimepoints, Jn.Ifthenumberofpoints tjn isverylarge,asforthemagnetometerorhighfrequency financialdata,expansion(1.3)servesthepracticalpurposeofreplacingthe originalscalardata Xn(tjn)byasmallercollectionofthecoefficients cnm. Ifthetimepoints tjn differbetweensubjects,theexpansionputsthecurves intoacommondomain,sothattheyaremorereadilycomparable.Foreach n,thecurve xn isrepresentedbythecolumnvector cn =[cn1,cn2,...,cnM ]T ofdimension M .Expansion(1.3)canalsobeviewedasapreliminarysmoothingofthecurves;ifthebasisfunctionsaresmooth,asisthecaseformost commonlyusedbasissystems,thentheright–handsideof(1.3)willinherit thissmoothness.However,additionalandmoretargetedsmoothing,sayfor parameterestimates,canbedonelateron.

Wenowdiscuss R implementation.The fda packageinRwasoriginally designedtoaccompanythebookofRamsayandSilverman(2005).Initlie thebuildingblockstocarryoutnearlyallofthemethodsdiscussedinthis book.Inadditiontothe fda package,the refund packagehasemergedwith alargecollectionofflexibletoolswhichwewilldiscusslateron.Afterloading thepackage fda usingthe RGui interface,usethefollowingcode

spline.basis=create.bspline.basis(rangeval=c(0,10), nbasis=5) plot(spline.basis, lty=1, lwd=2)

toproduce Figure1.3 whoseleftpanelshowsfiveB-splinebasisfunctions definedontheinterval[0, 10].Thereareadditionalargumentswhichspecify thedegreeofsmoothnessandthepositionofthebasisfunctions,weusedefault values.Thecode

fourier.basis=create.fourier.basis(rangeval=c(0,10), nbasis=5)

plot(fourier.basis, lty=1, lwd=2)

producestherightpanelof Figure1.3 whichshowsthefirstfiveFourierbasis functions.ThefirstfunctionintheFourierbasisistheconstantfunction, thentherearesineandcosinefunctionsofperiodequaltothelengthofthe interval.Thesearefollowedbysineandcosinefunctionsofdecreasingperiods or,equivalentlyincreasingfrequencies.Anoddnumberofbasisfunctionsis used:theconstantfunctionandsine/cosinepairs.Itisimportanttokeepin mindthattheFouriersystemisusuallyonlysuitableforfunctionswhichhave approximatelythesamevaluesatthebeginningandtheendoftheinterval; thisisdiscussedingreaterdetailin Section10.2.

Thefollowingexampleillustratestheconstructionofabasisexpansion usingsimulateddata.Thisallowsustofocusonessentialaspectswithout goingintopreprocessingofrealdata.Dataexamplesarepresentedlaterin thischapter.

Example1.1.1 [B-splineexpansionoftheWienerprocess]TheWienerprocess,alsoknownastheBrownianmotion,isdefinedin Section11.4. Itisan appropriatelimitoftherandomwalk

Figure1.4 showsatrajectoryoftherandomwalkwhichcanbeviewedas afunctiondefinedoninterval[0,K]by X(ti)= Si,ti = i.Noticesome similaritytothepricedatain Figure1.2. Inthecodebelow,thefunction smooth.basis isusedtocreateafunctionaldataobject Wiener.fd which containstheexpansioncoefficients cnm aswellasinformationaboutthebasis functionsusedtoexpandtherandomwalkfunction.Thefollowingcodewas usedtogenerate Figure1.4:

Wiener=cumsum(rnorm(10000))/100 #randomwalkon[0,K],K=10ˆ4 plot.ts(Wiener, xlab="", ylab="")

B25.basis=create.bspline.basis(rangeval=c(0,10000), nbasis=25) Wiener.fd=smooth.basis(y=Wiener, fdParobj=B25.basis) lines(Wiener.fd, lwd=3)

Chapter5 ofRamsay etal. (2009),andseveralchaptersinRamsayand Silverman(2005),describemoresophisticatedmethodsofconstructingfunctionaldataobjectsfromrawdata.Theseincludesmoothingwitharoughness penaltyandsmoothingwhichpreservesmonotonicityorpositivenessofthe data.Thelasttwotypesofsmoothingareeasytounderstandconceptually. Inmanystudies,dataaremeasurementsofthesizeofanindividualoran organwhichcannotdecreasewithtime.Similarly,somequantitiescanonly benonnegative.Ifoneappliesabasisexpansion(1.3)tosuchdata,onecan sometimesobtaincurveswhicharedecreasingornegativeonsmallintervals.

FIGURE1.4:Randomwalkanditsexpansion(1.3)using25B-splinebasis functions.

Customized R functionscanbeusedtoensurethattheoutputfunctionsare monotoneornonnegative.

1.2Samplemeanandcovariance

Wenowassumethattherawdatahavebeenconvertedtofunctionalobjects byasuitablebasisexpansion,possiblywithadditionalsmoothing,andwecan workwithfunctionaldataoftheform(1.2).Thesimplestsummarystatistics arethepointwisemeanandthepointwisestandarddeviation:

In Example1.2.1 weextend Example1.1.1 toillustratetheseconcepts.

Example1.2.1 [PointwisemeanandSD]Wesimulateasampleof N =50 randomwalksandconvertthemtofunctionalobjects,asexplainedin Example1.1.1. Wethenplotthem,calculatethepointwisemeanandSD,and

FIGURE1.5:Randomwalksconvertedtofunctionalobjectstogetherwiththe pointwisesampleSD(thickcontinuousline)andthepointwisemean(thick dashedline).

addthosetotheplot,see Figure1.5. Thefollowingcodewasusedtoproduce Figure1.5. Theoutputofthefunction smooth.basis isalist.Thevalues ofthefunctionsareextractedusing $fd.

N=50

W.mat=matrix(0, ncol=N, nrow=10000) for(nin1:N){W.mat[,n]=cumsum(rnorm(10000))/100} B25.basis=create.bspline.basis(rangeval=c(0,10000), nbasis=25)

W.fd=smooth.basis(y=W.mat, fdParobj=B25.basis) plot(W.fd, ylab="", xlab="",col="gray",lty=1)

W.mean=mean(W.fd$fd) W.sd=std.fd(W.fd$fd) lines(W.sd, lwd=3); lines(W.mean, lty=2, lwd=3)

Thepointwisesamplestandarddeviationgivesusanideaaboutthetypical variabilityofcurvesatanypoint t,butitgivesnoinformationonhowthe valuesofthecurvesatpoint t relatetothoseatpoint s.Anobjectwhichis extensivelyusedinFDAisthe samplecovariancefunction definedas

c(t,s)= 1 N 1 N n=1 Xn (t) XN (t) Xn (s) XN (s)

Theinterpretationofthevaluesofˆ c(t,s)isthesameasfortheusualvariancecovariancematrix.Forexample,largevaluesindicatethat Xn (t)and Xn (s)

IntroductiontoFunctionalDataAnalysis tendtobesimultaneouslyaboveorbelowtheaveragevaluesatthesepoints.

Example1.2.2 showshowtocalculatethebivariatefunctionˆ c(t,s),whichis abivariatefunctionaldataobject, bifd.

Example1.2.2 [Samplecovariancefunction]Weconsiderthe50random walksconvertedtofunctionalobjectsin Example1.2.1. Thefollowingcode computesthesamplecovariancefunctionsandgenerates Figure1.6. Inthis case,thecontourplotisparticularlyinteresting.Wewillseein Section11.4, Proposition11.4.1,thatthefunctionalpopulationparameterwhichthefunctionˆ c(t,s)estimatesisgivenby c(t,s)=min(t,s). #UsetheobjectW.fdgeneratedinthepreviousexample. W.cov=var.fd(W.fd$fd) # $fdextractsfunctionvalues grid=(1:100)*100 W.cov.mat=eval.bifd(grid,grid,W.cov) persp(grid,grid,W.cov.mat, xlab="s", ylab="t", zlab="c(s,t)") contour(grid,grid,W.cov.mat, lwd=2)

FIGURE1.6:Aperspectiveplot(top)andcontourplot(bottom)ofthecovariancefunctionofthesampleof50randomwalksfrom Example1.2.2.

1.3Principalcomponentfunctions

Oneofthemostusefulandoftenusedtoolsinfunctionaldataanalysisis theprincipalcomponentanalysis.Estimatedfunctionalprincipalcomponents, EFPC’s,arerelatedtothesamplecovariancefunctionˆ c(t,s),aswillbeexplainedin Sections11.4 and 12.2.Hereweonlyexplainhowtocomputeand interpretthem.

FIGURE1.7:Thefirstfourestimatedfunctionalprincipalcomponentsofthe 50randomwalksfrom Example1.2.2.

Inexpansion (1.3), thebasisfunctions Bm arefixed.Theideaofthefunctionalprincipalcomponentexpansionistofindfunctionsˆ vj suchthatthe centeredfunctions Xn XN arerepresentedas

with p muchsmallerthan M in(1.3).TheEFPC’sˆ vj arecomputedfrom theobservedfunctions X1,X2,...,XN afterconvertingthemtofunctional objects. Figure1.7 showstheEFPC’sˆ vj ,j =1, 2, 3, 4, computedforthe50 smoothedtrajectoriesoftherandomwalk.Theˆ vj resembletrigonometric functions,andwewillseein Sections11.4 and 12.2 thattheyindeedare estimatesofspecifictrigonometricfunctionswhoseclosedformcanbefound analytically.ThefirstEFPC,ˆ v1,plottedasthecontinuousblackline,shows

Firststepsintheanalysisoffunctionaldata 11 themostpronouncedpatternofthedeviationfromthemeanfunctionofa randomlyselectedtrajectory.Acursoryexaminationof Figure1.5 confirms thattheshapeofˆ v1 indeedsummarizesthemainpatternofvariabilityaround themeanfunctionwell.Foreachcurve Xn,thecoefficient ˆ ξn1 quantifiesthe contributionofˆ v1 toitsshape.Thecoefficient ˆ ξnj iscalledthe score of Xn withrespecttoˆ vj .ThesecondEFPC,plottedasthedashedredline,shows thesecondmostimportantmodeofdeparturefromthemeanfunctionsofthe 50randomwalkcurves.TheEFPC’sˆ vj are orthonormal,inthesensethat

ThisisauniversalpropertyoftheEFPC’swhichrestrictstheirinterpretability.Forexample,ˆ v2 isthesecondmostimportantmodeofvariabilitywhich is orthogonal toˆ v1

Wewillseein Chapter11 thatthetotalvariabilityofasampleofcurves aboutthesamplemeanfunction,canbedecomposedintothesumofvariabilitiesexplainedbyeachEFPC.Forthesampleofthe50randomwalks,thefirst EFPCˆ v1 explainsabout81%ofvariability,thesecondabout10%,thethird about4%andthefourthabout2%.TogetherthefirstfourEFPC’sexplain over96%ofvariability.Thisjustifiestheexpansionusing p =4,oreven p =2, asthecontributionoftheremainingcomponentstotheshapeofthecurves issmall.Thepercentageofthevariabilityexplainedbyˆ vj isrelatedtothe sizeofthescores ˆ ξnj ;thesmallerthepercentage,thesmallerthescores.The followingcodewasusedtoproduce Figure1.7 andcomputethepercentageof variabilityexplainedbyeachEFPC.

W.pca= pca.fd(W.fd$fd, nharm=4) plot(W.pca$harmonics, lwd=3)

W.pca$varprop [1]0.805131550.095091540.040994960.02119239

Intheremainingtwosectionsofthischapterwefurtherillustratethe conceptsintroducedsofarbyexaminingspecificdataapplications.

1.4AnalysisofBOAstockreturns

BankofAmerica,tickersymbolBOA,isoneofthelargestfinancialinstitutions intheworldandhasahistorygoingbackoveronehundredyears.Weconsider stockvalues,recordedeveryminute,fromApril9th,1997toApril2nd,2007. Eachtradingdaybeginsat9:30AM(EST)andendsat4:00PM,resulting in6.5hoursoftradingtime.Thuswecantake t (0, 6.5).Thisresultsin 2511daysworthofdata,witheachdayconsistingof390measurements.The functionalobservationweconsideristhe cumulativelog-return.If Pn(t)isthe

FIGURE1.8:PlotoffirsttencumulativelogreturnsforBOA.

valueofthestockonday n attime t,thenthecumulativelog-returnisgiven by Rn(t):=log(Pn(t)) log(Pn(0)) ≈

Thefunction Rn(t)depictshowaninvestment,madeatopening,evolvesover thecourseoftheday.Thefirst10suchdaysaregivenin Figure1.8. There isasubstantialoutlierthatoccursonAugust26th,2004,whichisduetoa stocksplitandisthusdiscardedfromfurtheranalysis.Theplotisgenerated usingtheRcommands:

BOA<-read.table("BOA.txt",header=TRUE)

Dates<-dimnames(BOA)[[1]]

BOA<-data.matrix(BOA)

Outlier<-which(Dates=="08/26/2004")

BOA<-BOA[-Outlier,]

N<-dim(BOA)[1]

M<-dim(BOA)[2]

Times<-seq(0,6.5,length=M)

log_BOA<-log(BOA)- matrix(log(BOA)[,1],nrow=N,ncol=M) bspline_basis<-create.bspline.basis(rangeval=c(0,6.5),norder =4,nbasis=200)

log_BOA_f<-Data2fd(Times,t(log_BOA),basisobj =bspline_basis) plot(log_BOA_f[1:10],xlab="",ylab="",lwd=1.5)

In Figure1.9 weplotthemeanfunctionand,usingthestandarddeviation function,weincludepoint-wise95%confidenceintervals.Thereturnshave asmallpositivemeanfunctionwhichincreasesrapidlyearlyinthedayand

Another random document with no related content on Scribd:

[256]Ib., p. 165.

[257]“Modern Abyssinia,” p 224

[258]Compare, e.g., his remark on p. 223, “They have any amount of pluck,” with Parkyns’s comments quoted on p. 24 of this book

[259]E.g. p. 222.

[260]Ib , p 216

[261]Eyre and Spottiswoode.

[262]Cf p 308

[263]Mr. Wylde describes the Ras as “by far the cleverest and most enlightened man that the country possesses.” He is a possible successor to the Abyssinian throne.

[264]Colonel Rochfort’s Report

APPENDIX

A is a deeply interesting country from the point of view of geographical distribution, and it is much to be regretted that Dr. A. J. Hayes did not have the opportunity of collecting insects on a large scale. The animals of the southern half of Arabia are Ethiopian in character; but in the Abyssinian mountains we may expect to find, and we do find, a certain amount of Oriental affinity.

The valuable little collection of insects made by Dr. Hayes has been presented by him to the Hope Department of the Oxford University Museum, where the specimens can be seen and studied by every naturalist interested in the great problems of distribution. The attention of the donor was directed to the Oxford Museum by Mr. W. L. S. Loat, who has himself contributed a large amount of valuable material. Dr. Hayes’ collection was made, in February 1903, in the vicinity of Lake Tsana, at a height of about 6500 feet. A complete list is furnished below. Dr. Dixey has kindly determined and made remarks upon the Pierinae.

LEPIDOPTERA.

NYMPHALIDAE.

D: 1 Limnas chrysippus (Linn.) ♀. The ground colour of the pale tint characteristic of Oriental specimens and usually replaced by a much darker shade in African.

D: 2 L. chrysippus (Linn.) var. alcippus (Cram.) ♂♂. Typical.

N: 1 Neptis agatha (Cram.). 1 Precis cebrene (Trim.).

PAPILIONIDAE.

P: 1 Catopsilia florella (Fabr.) ♂.

2 Colias electra (Linn.) ♂ ♀.

3 Terias brigitta (Cram.) ♂ ♂ ♀. Dry season forms; not extreme.

3 Eronia leda (Boisd.) ♂ ♀ ♀.

One of these females has an orange apical patch on the forewing, almost as distinct as that of the male.

1 Pinacopteryx sp. ?

A female, rather worn; simulating Mylothris agathina ♀.

Probably a new species, but being in poor condition and a single specimen it would not be advisable to describe it.

1 Belenois severina (Cram.) ♀. Dry season form.

1 Phrissura sp. ♂.

A male, of the P. sylvia group. This form of Phrissura has not previously been recorded from any part of East Africa.

P: 8 Papilio demodocus (Esp.).

HYMENOPTERA.

1 Dorylus fimbriatus (Shuck.) ♂.

COLEOPTERA.

LAMELLICORNIA.

S: 1 Oniticellus inaequalis (Reiche). Only known from Abyssinia.

C: 1 Pachnoda abyssinica (Blanch.).

1 Pachnoda stehelini (Schaum).

Both Abyssinian species.

PHYTOPHAGA.

C: 1 Aspidomorpha punctata (Fab.).

HETEROMERA.

C: 2 Mylabris, probably a new species.

NEUROPTERA.

1 Nemoptera, probably a new species.

ORTHOPTERA.

A: 1 Cyrtacanthacris sp.

1 Phymateus brunneri? (Bolivar).

1 Phymateus leprosus (Fab.).

1 Petasia anchoreta (Bolivar).

M: 1 Sphodromantis bioculata (Burm.).

1 Chiropus aestuans? (Sauss.).

In addition to the above, Dr. Hayes presented three insects captured by him at Gedaref in the Soudan, including a pair of a magnificent new species of Buprestid beetle of the genus Sternocera, taken in coitu. This species has recently been described, from Dr. Hayes’ specimen and two others in the British Museum, by Mr. C. O. Waterhouse, who has given it the name Sternocera druryi (“Ann. Mag. Nat. Hist.” Oct., 1904, p. 247). The third insect is an example of a Cantharid beetle, which does great damage to the crops at Gadarif. Its determination as Mylabris hybrida (Bohem.) is therefore a matter of some importance.

THE END

PRINTED BY WILLIAM CLOWES AND SONS, LIMITED, LONDON AND BECCLES.

THE ANGLO-EGYPTIAN SUDAN

By permission of the Egyptian Government.

(Large-size)

London: Smith, Elder & Co. Stanford’s Geogl Estabt., London.

LAKE TSANA

By permission of the Egyptian Government. London: Smith, Elder & Co.

(Large-size)

Stanford’s Geogl Estabt., London.

Transcriber's note:

pg 70 (footnote 41) Changed: Abyssinnia and its people to: Abyssinia

pg 91-92 (footnote 61) Changed: equitidœ to: equitidæ

pg 91-92 (footnote 61) Changed: nectariniœ to: nectariniæ

pg 96 Changed: plently of fish to: plenty

pg 271 Changed: been complied by to: compiled

pg 293 Changed: general langour to: languor

pg 311 (footnote 262) Changed: Cp. to: Cf.

Minor punctuation changes have been done silently.

Spelling inconsistencies have been left unchanged.

*** END OF THE PROJECT GUTENBERG EBOOK THE SOURCE OF THE BLUE NILE ***

Updated editions will replace the previous one—the old editions will be renamed.

Creating the works from print editions not protected by U.S. copyright law means that no one owns a United States copyright in these works, so the Foundation (and you!) can copy and distribute it in the United States without permission and without paying copyright royalties. Special rules, set forth in the General Terms of Use part of this license, apply to copying and distributing Project Gutenberg™ electronic works to protect the PROJECT GUTENBERG™ concept and trademark. Project Gutenberg is a registered trademark, and may not be used if you charge for an eBook, except by following the terms of the trademark license, including paying royalties for use of the Project Gutenberg trademark. If you do not charge anything for copies of this eBook, complying with the trademark license is very easy. You may use this eBook for nearly any purpose such as creation of derivative works, reports, performances and research. Project Gutenberg eBooks may be modified and printed and given away—you may do practically ANYTHING in the United States with eBooks not protected by U.S. copyright law. Redistribution is subject to the trademark license, especially commercial redistribution.

START: FULL LICENSE

THE FULL PROJECT GUTENBERG LICENSE

PLEASE READ THIS BEFORE YOU DISTRIBUTE OR USE THIS WORK

To protect the Project Gutenberg™ mission of promoting the free distribution of electronic works, by using or distributing this work (or any other work associated in any way with the phrase “Project Gutenberg”), you agree to comply with all the terms of the Full Project Gutenberg™ License available with this file or online at www.gutenberg.org/license.

Section 1. General Terms of Use and Redistributing Project Gutenberg™ electronic works

1.A. By reading or using any part of this Project Gutenberg™ electronic work, you indicate that you have read, understand, agree to and accept all the terms of this license and intellectual property (trademark/copyright) agreement. If you do not agree to abide by all the terms of this agreement, you must cease using and return or destroy all copies of Project Gutenberg™ electronic works in your possession. If you paid a fee for obtaining a copy of or access to a Project Gutenberg™ electronic work and you do not agree to be bound by the terms of this agreement, you may obtain a refund from the person or entity to whom you paid the fee as set forth in paragraph 1.E.8.

1.B. “Project Gutenberg” is a registered trademark. It may only be used on or associated in any way with an electronic work by people who agree to be bound by the terms of this agreement. There are a few things that you can do with most Project Gutenberg™ electronic works even without complying with the full terms of this agreement. See paragraph 1.C below. There are a lot of things you can do with Project Gutenberg™ electronic works if you follow the terms of this agreement and help preserve free future access to Project Gutenberg™ electronic works. See paragraph 1.E below.

1.C. The Project Gutenberg Literary Archive Foundation (“the Foundation” or PGLAF), owns a compilation copyright in the collection of Project Gutenberg™ electronic works. Nearly all the individual works in the collection are in the public domain in the United States. If an individual work is unprotected by copyright law in the United States and you are located in the United States, we do not claim a right to prevent you from copying, distributing, performing, displaying or creating derivative works based on the work as long as all references to Project Gutenberg are removed. Of course, we hope that you will support the Project Gutenberg™ mission of promoting free access to electronic works by freely sharing Project Gutenberg™ works in compliance with the terms of this agreement for keeping the Project Gutenberg™ name associated with the work. You can easily comply with the terms of this agreement by keeping this work in the same format with its attached full Project Gutenberg™ License when you share it without charge with others.

1.D. The copyright laws of the place where you are located also govern what you can do with this work. Copyright laws in most countries are in a constant state of change. If you are outside the United States, check the laws of your country in addition to the terms of this agreement before downloading, copying, displaying, performing, distributing or creating derivative works based on this work or any other Project Gutenberg™ work. The Foundation makes no representations concerning the copyright status of any work in any country other than the United States.

1.E. Unless you have removed all references to Project Gutenberg:

1.E.1. The following sentence, with active links to, or other immediate access to, the full Project Gutenberg™ License must appear prominently whenever any copy of a Project Gutenberg™ work (any work on which the phrase “Project Gutenberg” appears, or with which the phrase “Project

Gutenberg” is associated) is accessed, displayed, performed, viewed, copied or distributed:

This eBook is for the use of anyone anywhere in the United States and most other parts of the world at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org. If you are not located in the United States, you will have to check the laws of the country where you are located before using this eBook.

1.E.2. If an individual Project Gutenberg™ electronic work is derived from texts not protected by U.S. copyright law (does not contain a notice indicating that it is posted with permission of the copyright holder), the work can be copied and distributed to anyone in the United States without paying any fees or charges. If you are redistributing or providing access to a work with the phrase “Project Gutenberg” associated with or appearing on the work, you must comply either with the requirements of paragraphs 1.E.1 through 1.E.7 or obtain permission for the use of the work and the Project Gutenberg™ trademark as set forth in paragraphs 1.E.8 or 1.E.9.

1.E.3. If an individual Project Gutenberg™ electronic work is posted with the permission of the copyright holder, your use and distribution must comply with both paragraphs 1.E.1 through 1.E.7 and any additional terms imposed by the copyright holder. Additional terms will be linked to the Project Gutenberg™ License for all works posted with the permission of the copyright holder found at the beginning of this work.

1.E.4. Do not unlink or detach or remove the full Project Gutenberg™ License terms from this work, or any files containing a part of this work or any other work associated with Project Gutenberg™.

1.E.5. Do not copy, display, perform, distribute or redistribute this electronic work, or any part of this electronic work, without prominently displaying the sentence set forth in paragraph 1.E.1 with active links or immediate access to the full terms of the Project Gutenberg™ License.

1.E.6. You may convert to and distribute this work in any binary, compressed, marked up, nonproprietary or proprietary form, including any word processing or hypertext form. However, if you provide access to or distribute copies of a Project Gutenberg™ work in a format other than “Plain Vanilla ASCII” or other format used in the official version posted on the official Project Gutenberg™ website (www.gutenberg.org), you must, at no additional cost, fee or expense to the user, provide a copy, a means of exporting a copy, or a means of obtaining a copy upon request, of the work in its original “Plain Vanilla ASCII” or other form. Any alternate format must include the full Project Gutenberg™ License as specified in paragraph 1.E.1.

1.E.7. Do not charge a fee for access to, viewing, displaying, performing, copying or distributing any Project Gutenberg™ works unless you comply with paragraph 1.E.8 or 1.E.9.

1.E.8. You may charge a reasonable fee for copies of or providing access to or distributing Project Gutenberg™ electronic works provided that:

• You pay a royalty fee of 20% of the gross profits you derive from the use of Project Gutenberg™ works calculated using the method you already use to calculate your applicable taxes. The fee is owed to the owner of the Project Gutenberg™ trademark, but he has agreed to donate royalties under this paragraph to the Project Gutenberg Literary Archive Foundation. Royalty payments must be paid within 60 days following each date on which you prepare (or are legally required to prepare) your periodic tax returns. Royalty payments should be clearly marked as such and sent to the Project Gutenberg Literary Archive Foundation at the address specified in Section 4, “Information

about donations to the Project Gutenberg Literary Archive Foundation.”

• You provide a full refund of any money paid by a user who notifies you in writing (or by e-mail) within 30 days of receipt that s/he does not agree to the terms of the full Project Gutenberg™ License. You must require such a user to return or destroy all copies of the works possessed in a physical medium and discontinue all use of and all access to other copies of Project Gutenberg™ works.

• You provide, in accordance with paragraph 1.F.3, a full refund of any money paid for a work or a replacement copy, if a defect in the electronic work is discovered and reported to you within 90 days of receipt of the work.

• You comply with all other terms of this agreement for free distribution of Project Gutenberg™ works.

1.E.9. If you wish to charge a fee or distribute a Project Gutenberg™ electronic work or group of works on different terms than are set forth in this agreement, you must obtain permission in writing from the Project Gutenberg Literary Archive Foundation, the manager of the Project Gutenberg™ trademark. Contact the Foundation as set forth in Section 3 below.

1.F.

1.F.1. Project Gutenberg volunteers and employees expend considerable effort to identify, do copyright research on, transcribe and proofread works not protected by U.S. copyright law in creating the Project Gutenberg™ collection. Despite these efforts, Project Gutenberg™ electronic works, and the medium on which they may be stored, may contain “Defects,” such as, but not limited to, incomplete, inaccurate or corrupt data, transcription errors, a copyright or other intellectual property infringement, a defective or damaged disk or other

medium, a computer virus, or computer codes that damage or cannot be read by your equipment.

1.F.2. LIMITED WARRANTY, DISCLAIMER OF DAMAGESExcept for the “Right of Replacement or Refund” described in paragraph 1.F.3, the Project Gutenberg Literary Archive Foundation, the owner of the Project Gutenberg™ trademark, and any other party distributing a Project Gutenberg™ electronic work under this agreement, disclaim all liability to you for damages, costs and expenses, including legal fees. YOU AGREE THAT YOU HAVE NO REMEDIES FOR NEGLIGENCE, STRICT LIABILITY, BREACH OF WARRANTY OR BREACH OF CONTRACT EXCEPT THOSE PROVIDED IN PARAGRAPH

1.F.3. YOU AGREE THAT THE FOUNDATION, THE TRADEMARK OWNER, AND ANY DISTRIBUTOR UNDER THIS AGREEMENT WILL NOT BE LIABLE TO YOU FOR ACTUAL, DIRECT, INDIRECT, CONSEQUENTIAL, PUNITIVE OR INCIDENTAL DAMAGES EVEN IF YOU GIVE NOTICE OF THE POSSIBILITY OF SUCH DAMAGE.

1.F.3. LIMITED RIGHT OF REPLACEMENT OR REFUND - If you discover a defect in this electronic work within 90 days of receiving it, you can receive a refund of the money (if any) you paid for it by sending a written explanation to the person you received the work from. If you received the work on a physical medium, you must return the medium with your written explanation. The person or entity that provided you with the defective work may elect to provide a replacement copy in lieu of a refund. If you received the work electronically, the person or entity providing it to you may choose to give you a second opportunity to receive the work electronically in lieu of a refund. If the second copy is also defective, you may demand a refund in writing without further opportunities to fix the problem.

1.F.4. Except for the limited right of replacement or refund set forth in paragraph 1.F.3, this work is provided to you ‘AS-IS’, WITH NO OTHER WARRANTIES OF ANY KIND, EXPRESS

OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY PURPOSE.

1.F.5. Some states do not allow disclaimers of certain implied warranties or the exclusion or limitation of certain types of damages. If any disclaimer or limitation set forth in this agreement violates the law of the state applicable to this agreement, the agreement shall be interpreted to make the maximum disclaimer or limitation permitted by the applicable state law. The invalidity or unenforceability of any provision of this agreement shall not void the remaining provisions.

1.F.6. INDEMNITY - You agree to indemnify and hold the Foundation, the trademark owner, any agent or employee of the Foundation, anyone providing copies of Project Gutenberg™ electronic works in accordance with this agreement, and any volunteers associated with the production, promotion and distribution of Project Gutenberg™ electronic works, harmless from all liability, costs and expenses, including legal fees, that arise directly or indirectly from any of the following which you do or cause to occur: (a) distribution of this or any Project Gutenberg™ work, (b) alteration, modification, or additions or deletions to any Project Gutenberg™ work, and (c) any Defect you cause.

Section 2. Information about the Mission of Project Gutenberg™

Project Gutenberg™ is synonymous with the free distribution of electronic works in formats readable by the widest variety of computers including obsolete, old, middle-aged and new computers. It exists because of the efforts of hundreds of volunteers and donations from people in all walks of life.

Volunteers and financial support to provide volunteers with the assistance they need are critical to reaching Project

Gutenberg™’s goals and ensuring that the Project Gutenberg™ collection will remain freely available for generations to come. In 2001, the Project Gutenberg Literary Archive Foundation was created to provide a secure and permanent future for Project Gutenberg™ and future generations. To learn more about the Project Gutenberg Literary Archive Foundation and how your efforts and donations can help, see Sections 3 and 4 and the Foundation information page at www.gutenberg.org.

Section 3. Information about the Project Gutenberg Literary Archive Foundation

The Project Gutenberg Literary Archive Foundation is a nonprofit 501(c)(3) educational corporation organized under the laws of the state of Mississippi and granted tax exempt status by the Internal Revenue Service. The Foundation’s EIN or federal tax identification number is 64-6221541. Contributions to the Project Gutenberg Literary Archive Foundation are tax deductible to the full extent permitted by U.S. federal laws and your state’s laws.

The Foundation’s business office is located at 809 North 1500 West, Salt Lake City, UT 84116, (801) 596-1887. Email contact links and up to date contact information can be found at the Foundation’s website and official page at www.gutenberg.org/contact

Section 4. Information about Donations to the Project Gutenberg Literary Archive Foundation

Project Gutenberg™ depends upon and cannot survive without widespread public support and donations to carry out its mission of increasing the number of public domain and licensed works that can be freely distributed in machine-readable form

accessible by the widest array of equipment including outdated equipment. Many small donations ($1 to $5,000) are particularly important to maintaining tax exempt status with the IRS.

The Foundation is committed to complying with the laws regulating charities and charitable donations in all 50 states of the United States. Compliance requirements are not uniform and it takes a considerable effort, much paperwork and many fees to meet and keep up with these requirements. We do not solicit donations in locations where we have not received written confirmation of compliance. To SEND DONATIONS or determine the status of compliance for any particular state visit www.gutenberg.org/donate.

While we cannot and do not solicit contributions from states where we have not met the solicitation requirements, we know of no prohibition against accepting unsolicited donations from donors in such states who approach us with offers to donate.

International donations are gratefully accepted, but we cannot make any statements concerning tax treatment of donations received from outside the United States. U.S. laws alone swamp our small staff.

Please check the Project Gutenberg web pages for current donation methods and addresses. Donations are accepted in a number of other ways including checks, online payments and credit card donations. To donate, please visit: www.gutenberg.org/donate.

Section 5. General Information About Project Gutenberg™ electronic works

Professor Michael S. Hart was the originator of the Project Gutenberg™ concept of a library of electronic works that could be freely shared with anyone. For forty years, he produced and

distributed Project Gutenberg™ eBooks with only a loose network of volunteer support.

Project Gutenberg™ eBooks are often created from several printed editions, all of which are confirmed as not protected by copyright in the U.S. unless a copyright notice is included. Thus, we do not necessarily keep eBooks in compliance with any particular paper edition.

Most people start at our website which has the main PG search facility: www.gutenberg.org.

This website includes information about Project Gutenberg™, including how to make donations to the Project Gutenberg Literary Archive Foundation, how to help produce our new eBooks, and how to subscribe to our email newsletter to hear about new eBooks.

Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.