Verfügbarkeit: Chemometrics with R

Chemometrics with R: multivariate data analysis in the natural sciences and life sciences

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Bibliographische Detailangaben
1. Verfasser:	Wehrens, Ron (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Berlin [u.a.] Springer 2011
Schriftenreihe:	Use R!
Schlagworte:	R > Programm Multivariate Analyse Chemometrie Paperback / softback Upper undergraduate Bioinformatics Chemometrics Multivariate statistics R software
Online-Zugang:	BTU01 TUM01 UBA01 UBM01 UBT01 UBW01 UER01 UPA01 Volltext Inhaltsverzeichnis
Beschreibung:	1 Online-Ressource (XIV, 285 S.) 99 schw.-w. Ill., 1 schw.-w. Tab.
ISBN:	9783642178412
DOI:	10.1007/978-3-642-17841-2

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Datensatz im Suchindex

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adam_text	IMAGE 1 CONTENTS 1 INTRODUCTION 1 PART I PRELIMINARIES 2 DATA 7 3 PREPROCESSING 13 3.1 DEALING WITH NOISE 13 3.2 BASELINE REMOVAL 18 3.3 ALIGNING PEAKS - WARPING 20 3.3.1 PARAMETRIC TIME WARPING 22 3.3.2 DYNAMIC TIME WARPING 26 3.3.3 PRACTICALITIES 31 3.4 PEAK PICKING 31 3.5 SCALING 33 3.6 MISSING DATA 38 3.7 CONCLUSION 39 PART II EXPLORATORY ANALYSIS 4 PRINCIPAL COMPONENT ANALYSIS 43 4.1 THE MACHINERY 44 4.2 DOING IT YOURSELF 46 4.3 CHOOSING THE NUMBER OF PCS 48 4.3.1 STATISTICAL TESTS 49 4.4 PROJECTIONS 51 4.5 R FUNCTIONS FOR PCA 53 4.6 RELATED METHODS 57 4.6.1 MULTIDIMENSIONAL SCALING 57 BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1009481088 DIGITALISIERT DURCH IMAGE 2 XII CONTENTS 4.6.2 INDEPENDENT COMPONENT ANALYSIS AND PROJECTION PURSUIT 60 4.6.3 FACTOR ANALYSIS 63 4.6.4 DISCUSSION 65 5 SELF-ORGANIZING MAPS 67 5.1 TRAINING SOMS 68 5.2 VISUALIZATION 71 5.3 APPLICATION 73 5.4 R PACKAGES FOR SOMS 76 5.5 DISCUSSION 77 6 CLUSTERING 79 6.1 HIERARCHICAL CLUSTERING 80 6.2 PARTITIONAL CLUSTERING 85 6.2.1 K-MEANS 85 6.2.2 K-MEDOIDS 87 6.3 PROBABILISTIC CLUSTERING 90 6.4 COMPARING CLUSTERINGS 95 6.5 DISCUSSION 97 PART III MODELLING 7 CLASSIFICATION 103 7.1 DISCRIMINANT ANALYSIS 104 7.1.1 LINEAR DISCRIMINANT ANALYSIS 105 7.1.2 CROSSVALIDATION 109 7.1.3 FISHER LDA I LL 7.1.4 QUADRATIC DISCRIMINANT ANALYSIS 114 7.1.5 MODEL-BASED DISCRIMINANT ANALYSIS 116 7.1.6 REGULARIZED FORMS OF DISCRIMINANT ANALYSIS 118 7.2 NEAREST-NEIGHBOUR APPROACHES 122 7.3 TREE-BASED APPROACHES 126 7.3.1 RECURSIVE PARTITIONING AND REGRESSION TREES 126 7.3.2 DISCUSSION 135 7.4 MORE COMPLICATED TECHNIQUES 135 7.4.1 SUPPORT VECTOR MACHINES 136 7.4.2 ARTIFICIAL NEURAL NETWORKS 141 8 MULTIVARIATE REGRESSION 145 8.1 MULTIPLE REGRESSION 145 8.1.1 LIMITS OF MULTIPLE REGRESSION 147 8.2 PCR 149 8.2.1 THE ALGORITHM 149 IMAGE 3 CONTENTS XIII 8.2.2 SELECTING THE OPTIMAL NUMBER OF COMPONENTS 152 8.3 PARTIAL LEAST SQUARES (PLS) REGRESSION 155 8.3.1 THE ALGORITHM(S) 156 8.3.2 INTERPRETATION 160 8.4 RIDGE REGRESSION 163 8.5 CONTINUUM METHODS 165 8.6 SOME NON-LINEAR REGRESSION TECHNIQUES 165 8.6.1 SVMS FOR REGRESSION 165 8.6.2 ANNS FOR REGRESSION 168 8.7 CLASSIFICATION AS A REGRESSION PROBLEM 170 8.7.1 REGRESSION FOR LDA 170 8.7.2 DISCUSSION 172 P A RT IV MODEL INSPECTION 9 VALIDATION 175 9.1 REPRESENTATIVITY AND INDEPENDENCE 176 9.2 ERROR MEASURES 178 9.3 MODEL SELECTION 179 9.4 CROSSVALIDATION REVISITED 181 9.4.1 LOO CROSSVALIDATION 181 9.4.2 LEAVE-MULTIPLE-OUT CROSSVALIDATION 183 9.4.3 DOUBLE CROSSVALIDATION 183 9.5 THE JACKKNIFE 184 9.6 THE BOOTSTRAP 186 9.6.1 ERROR ESTIMATION WITH THE BOOTSTRAP 187 9.6.2 CONFIDENCE INTERVALS FOR REGRESSION COEFFICIENTS 190 9.6.3 OTHER R PACKAGES FOR BOOTSTRAPPING 195 9.7 INTEGRATED MODELLING AND VALIDATION 195 9.7.1 BAGGING 196 9.7.2 RANDOM FORESTS 197 9.7.3 BOOSTING 202 10 VARIABLE SELECTION 205 10.1 TESTS FOR COEFFICIENT SIGNIFICANCE 206 10.1.1 CONFIDENCE INTERVALS FOR INDIVIDUAL COEFFICIENTS 207 10.1.2 TESTS BASED ON OVERALL ERROR CONTRIBUTIONS 210 10.2 EXPLICIT COEFFICIENT PENALIZATION 213 10.3 GLOBAL OPTIMIZATION METHODS 217 10.3.1 SIMULATED ANNEALING 218 10.3.2 GENETIC ALGORITHMS 225 10.3.3 DISCUSSION 232 IMAGE 4 XIV CONTENTS PART V APPLICATIONS 11 CHEMOMETRIC APPLICATIONS 235 11.1 OUTLIER DETECTION WITH ROBUST PCA 235 11.1.1 ROBUST PCA 236 11.1.2 DISCUSSION 240 11.2 ORTHOGONAL SIGNAL CORRECTION AND OPLS 240 11.3 DISCRIMINATION WITH FAT DATA MATRICES 243 11.3.1 PCDA 244 11.3.2 PLSDA 248 11.4 CALIBRATION TRANSFER 251 11.5 MULTIVARIATE CURVE RESOLUTION 255 11.5.1 THEORY 256 11.5.2 FINDING SUITABLE INITIAL ESTIMATES 257 11.5.3 APPLYING MCR 261 11.5.4 CONSTRAINTS 263 11.5.5 COMBINING DATA SETS 265 PART VI APPENDICES R PACKAGES USED IN THIS BOOK 271 REFERENCES 273 INDEX 283
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spelling	Wehrens, Ron Verfasser aut Chemometrics with R multivariate data analysis in the natural sciences and life sciences Ron Wehrens Berlin [u.a.] Springer 2011 1 Online-Ressource (XIV, 285 S.) 99 schw.-w. Ill., 1 schw.-w. Tab. txt rdacontent c rdamedia cr rdacarrier Use R! R Programm (DE-588)4705956-4 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Chemometrie (DE-588)4299578-4 gnd rswk-swf Paperback / softback Upper undergraduate Bioinformatics Chemometrics Multivariate statistics R software Chemometrie (DE-588)4299578-4 s Multivariate Analyse (DE-588)4040708-1 s R Programm (DE-588)4705956-4 s 1\p DE-604 Erscheint auch als Druck-Ausgabe, Paperback 3-642-17840-5 Erscheint auch als Druck-Ausgabe, Paperback 978-3-642-17840-5 https://doi.org/10.1007/978-3-642-17841-2 Verlag Volltext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=021176234&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk
spellingShingle	Wehrens, Ron Chemometrics with R multivariate data analysis in the natural sciences and life sciences R Programm (DE-588)4705956-4 gnd Multivariate Analyse (DE-588)4040708-1 gnd Chemometrie (DE-588)4299578-4 gnd
subject_GND	(DE-588)4705956-4 (DE-588)4040708-1 (DE-588)4299578-4
title	Chemometrics with R multivariate data analysis in the natural sciences and life sciences
title_auth	Chemometrics with R multivariate data analysis in the natural sciences and life sciences
title_exact_search	Chemometrics with R multivariate data analysis in the natural sciences and life sciences
title_full	Chemometrics with R multivariate data analysis in the natural sciences and life sciences Ron Wehrens
title_fullStr	Chemometrics with R multivariate data analysis in the natural sciences and life sciences Ron Wehrens
title_full_unstemmed	Chemometrics with R multivariate data analysis in the natural sciences and life sciences Ron Wehrens
title_short	Chemometrics with R
title_sort	chemometrics with r multivariate data analysis in the natural sciences and life sciences
title_sub	multivariate data analysis in the natural sciences and life sciences
topic	R Programm (DE-588)4705956-4 gnd Multivariate Analyse (DE-588)4040708-1 gnd Chemometrie (DE-588)4299578-4 gnd
topic_facet	R Programm Multivariate Analyse Chemometrie
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