Multivariate statistical methods: a primer
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press
2017
|
| Ausgabe: | Fourth edition |
| Schriftenreihe: | A Chapman and Hall Book
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | xv, 253 Seiten Illustrationen |
| ISBN: | 9781498728966 |
Internformat
MARC
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| 264 | 1 | |a Boca Raton |b CRC Press |c 2017 | |
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| 500 | |a Includes bibliographical references and index | ||
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents
Preface..........................................................xiii
Authors............................................................xv
Chapter 1 The material of multivariate analysis....................1
1.1 Examples of multivariate data..................................1
1.2 Preview of multivariate methods...............................10
1.3 The multivariate normal distribution..........................14
1.4 Computer programs.............................................15
References.........................................................15
Appendix: An Introduction to R.....................................16
References......................................................27
Chapter 2 Matrix algebra......................................... 29
2.1 The need for matrix algebra...................................29
2.2 Matrices and vectors..........................................29
2.3 Operations on matrices........................................31
2.4 Matrix inversion..............................................33
2.5 Quadratic forms...............................................34
2.6 Eigenvalues and eigenvectors..................................34
2.7 Vectors of means and covariance matrices......................35
2.8 Further reading...............................................37
References.........................................................37
Appendix: Matrix Algebra in R......................................38
Chapter 3 Displaying multivariate data.............................41
3.1 The problem of displaying many variables in two dimensions....41
3.2 Plotting index variables......................................41
3.3 The draftsman s plot..........................................43
3.4 The representation of individual data points..................44
3.5 Profiles of variables.........................................46
3.6 Discussion and further reading................................47
References........................................................ 48
ix
X
Contents
Appendix: Producing Plots in R..................................49
References....................................................51
Chapter 4 Tests of significance with multivariate data..........53
4.1 Simultaneous tests on several variables....................53
4.2 Comparison of mean values for two samples: The single-
variable case...................................................53
4.3 Comparison of mean values for two samples: The
multivariate case..........................................55
4.4 Multivariate versus univariate tests.......................59
4.5 Comparison of variation for two samples: The single-variable
case.......................................................60
4.6 Comparison of variation for two samples: The multivariate
case.......................................................61
4.7 Comparison of means for several samples....................66
4.8 Comparison of variation for several samples................70
4.9 Computer programs..........................................74
References......................................................78
Appendix: Tests of Significance in R............................79
References................................................... 81
Chapter 5 Measuring and testing multivariate distances......... 83
5.1 Multivariate distances.....................................83
5.2 Distances between individual observations................ 83
5.3 Distances between populations and samples..................86
5.4 Distances based on proportions.............................91
5.5 Presence-absence data......................................92
5.6 The Mantel randomization test..............................93
5.7 Computer programs..........................................97
5.8 Discussion and further reading.............................97
References......................................................98
Appendix: Multivariate distance measures in R................ 100
References................................................... 101
Chapter 6 Principal components analysis.................... 103
6.1 Definition of principal components........................103
6.2 Procedure for a principal components analysis........... 104
6.3 Computer programs.........................................113
6.4 Further reading......................................... 114
References..................................................... 117
Appendix: Principal Components Analysis (PCA) in R.............118
References...................................................119
Contents
xi
Chapter 7 Factor analysis........................................121
7.1 The factor analysis model...................................121
7.2 Procedure for a factor analysis.............................124
7.3 Principal components factor analysis........................126
7.4 Using a factor analysis program to do principal components
analysis...................................................128
7.5 Options in analyses.........................................133
7.6 The value of factor analysis................................134
7.7 Discussion and further reading..............................134
References.......................................................135
Appendix: Factor Analysis in R...................................136
References....................................................137
Chapter 8 Discriminant function analysis....................... 139
8.1 The problem of separating groups............................139
8.2 Discrimination using Mahalanobis distances..................139
8.3 Canonical discriminant functions............................140
8.4 Tests of significance.......................................142
8.5 Assumptions.................................................143
8.6 Allowing for prior probabilities of group membership........148
8.7 Stepwise discriminant function analysis................... 150
8.8 Jackknife classification of individuals.....................150
8.9 Assigning ungrouped individuals to groups...................151
8.10 Logistic regression.........................................151
8.11 Computer programs...........................................156
8.12 Discussion and further reading..............................157
References.......................................................157
Appendix: Discriminant Function Analysis in R....................159
References....................................................162
Chapter 9 Cluster analysis..................................... 163
9.1 Uses of cluster analysis....................................163
9.2 Types of cluster analysis...................................163
9.3 Hierarchic methods..........................................164
9.4 Problems with cluster analysis............................ 166
9.5 Measures of distance........................................167
9.6 Principal components analysis with cluster analysis.........168
9.7 Computer programs...........................................172
9.8 Discussion and further reading..............................173
References..................................................... 177
Appendix: Cluster Analysis in R..................................178
Reference.....................................................179
Contents
xii
Chapter 10 Canonical correlation analysis......................181
10.1 Generalizing a multiple regression analysis...............181
10.2 Procedure for a canonical correlation analysis............183
10.3 Tests of significance.....................................184
10.4 Interpreting canonical variates...........................185
10.5 Computer programs.........................................197
10.6 Further reading...........................................197
References.....................................................199
Appendix: Canonical Correlation in R...........................200
References..................................................201
Chapter 11 Multidimensional scaling............................203
11.1 Constructing a map from a distance matrix.................203
11.2 Procedure for multidimensional scaling....................204
11.3 Computer programs.........................................214
11.4 Further reading...........................................214
References.....................................................215
Appendix: Multidimensional scaling in R........................216
References..................................................217
Chapter 12 Ordination........................................ 219
12.1 The ordination problem....................................219
12.2 Principal components analysis........................... 220
12.3 Principal coordinates analysis............................225
12.4 Multidimensional scaling..................................231
12.5 Correspondence analysis...................................233
12.6 Comparison of ordination methods..........................238
12.7 Computer programs.........................................239
12.8 Further reading...........................................239
References.....................................................240
Appendix: Ordination methods in R..............................241
References..................................................243
Chapter 13 Epilogue.......................................... 245
13.1 The next step.............................................245
13.2 Some general reminders....................................245
13.3 Missing values.......................................... 246
References.....................................................247
Index
249
|
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| isbn | 9781498728966 |
| language | English |
| lccn | 016020181 |
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| spelling | Manly, Bryan F. J. 1944- Verfasser (DE-588)131634062 aut Multivariate statistical methods a primer Fourth edition Boca Raton CRC Press 2017 xv, 253 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier A Chapman and Hall Book Includes bibliographical references and index Multivariate analysis Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf (DE-588)4151278-9 Einführung gnd-content Multivariate Analyse (DE-588)4040708-1 s DE-604 Navarro Alberto, Jorge A. 1963- Verfasser (DE-588)1118871022 aut Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029246293&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Multivariate statistical methods a primer |
| title_auth | Multivariate statistical methods a primer |
| title_exact_search | Multivariate statistical methods a primer |
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| title_fullStr | Multivariate statistical methods a primer |
| title_full_unstemmed | Multivariate statistical methods a primer |
| title_short | Multivariate statistical methods |
| title_sort | multivariate statistical methods a primer |
| title_sub | a primer |
| topic | Multivariate analysis Multivariate Analyse (DE-588)4040708-1 gnd |
| topic_facet | Multivariate analysis Multivariate Analyse Einführung |
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