Applied multivariate statistical analysis:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2019]
|
| Ausgabe: | Fifth edition |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xii, 558 Seiten Illustrationen, Diagramme (teilweise farbig) 235 mm x 155 mm |
| ISBN: | 9783030260057 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Contents Part I 1 Descriptive Techniques Comparison of Batches............................................................................. 1.1 Boxplots.......................................................................................... 1.2 Histograms.................................................. 1.3 Kernel Densities............................................................................ 1.4 Scatterplots...................................................................................... 1.5 Chemoff-Flury Faces...................................................................... 1.6 Andrews’ Curves.......................................................................... 1.7 Parallel Coordinate Plots............................................................... 1.8 Hexagon Plots ............................................................................... 1.9 Boston Housing............................................................................. 1.10 Exercises........................................................................................ References.................................................................................................... Part П 3 4 11 13 18 21 23 27 32 35 42 43 Multivariate Random Variables 2 A Short Excursion into Matrix Algebra............................................... 2.1 Elementary Operations ................................................................. 2.2 Spectral Decompositions............................................................... 2.3 Quadratic
Forms.......................................................................... . 2.4 Derivatives...................................................................................... 2.5 Partitioned Matrices ...................................................................... 2.6 Geometrical Aspects...................................................................... 2.7 Exercises........................................................................................ 47 47 53 55 58 59 61 68 3 Moving to Higher Dimensions................................................................. 3.1 Covariance...................................................................................... 3.2 Correlation...................................................................................... 71 72 76 vii
viii Contents 3.3 Summary Statistics........................................................................ 3.4 Linear Model for Two Variables................................................. 3.5 Simple Analysis of Variance........................................................ 3.6 Multiple Linear Model................................................................. 3.7 Boston Housing............................................................................. 3.8 Exercises......................................................................................... References.................................................................................................... 81 84 91 95 100 103 105 4 Multivariate Distributions........................................................................ 4.1 Distribution and Density Function............................................... 4.2 Moments and Characteristic Functions........................................ 4.3 Transformations............................................................................. 4.4 The Multinormal Distribution ...................................................... 4.5 Sampling Distributions and Limit Theorems.............................. 4.6 Heavy-Tailed Distributions.......................................................... 4.7 Copulae............................................ 4.8 Bootstrap......................................................................................... 4.9 Exercises.........................
References.................................................................................................... 107 108 113 123 125 129 135 151 161 164 166 5 Theory of the Multinormal...................................................................... 5.1 Elementary Properties of the Multinormal................................... 5.2 The Wishart Distribution............................................................... 5.3 Hotelling’s Г2-Distribution .......................................................... 5.4 Spherical and Elliptical Distributions.......................................... 5.5 Exercises......................... References.................................................................................................... 167 167 174 176 178 180 182 6 Theory of Estimation............................................................................... 6.1 The Likelihood Function............................................................... 6.2 The Cramer-Rao Lower Bound................................................... 6.3 Exercises............................ Reference...................................................................................................... 183 184 188 192 193 7 Hypothesis Testing.................................................................................... 195 7.1 Likelihood Ratio Test.................................................................... 196 7.2 Linear Hypothesis........................................................................... 205 7.3 Boston
Housing............................................................................. 222 7.4 Exercises......................................................................................... 225 References.................................................................................................... 229
Contents Part Ш ix Multivariate Techniques 8 Regression Models ................................................................................... 8.1 General ANOVA and ANCOVA Models................................... 8.1.1 ANOVA Models .......................................................... 8.1.2 ANCOVA Models........................................................ 8.1.3 Boston Housing............................................................ 8.2 Categorical Responses................................................................... 8.2.1 Multinomial Sampling and Contingency Tables .... 8.2.2 Log-Linear Models for Contingency Tables.............. 8.2.3 Testing Issues with Count Data................................... 8.2.4 Logit Models................................................................. 8.3 Exercises........................................................................................ Reference...................................................................................................... 233 235 235 240 242 243 243 244 248 251 258 259 9 Variable Selection...................................................................................... 9.1 Lasso............................................................................................... 9.1.1 Lasso in the Linear Regression Model....................... 9.1.2 Lasso in High Dimensions.......................................... 9.1.3 Lasso in Logit Model................................................... 9.2 Elastic
Net...................................................................................... 9.2.1 Elastic Net in Linear Regression Model..................... 9.2.2 Elastic Net in Logit Model.......................................... 9.3 Group Lasso................................................................................... 9.4 Exercises........................................................................................ References.................................................................................................... 261 262 262 271 272 276 277 278 279 282 283 10 Decomposition of Data Matrices by Factors....................................... 10.1 The Geometric Point of View..................................................... 10.2 Fitting the ¿»-Dimensional Point Cloud......................................... 10.3 Fitting the n-Dimensional Point Cloud........................................ 10.4 Relations Between Subspaces ..................................................... 10.5 Practical Computation................................................................... 10.6 Exercises........................................................................................ 285 286 287 290 292 293 296 11 Principal Components Analysis............................................................... 11.1 Standardized Linear Combination................................................. 11.2 Principal Components in Practice................................................. 11.3 Interpretation of the PCs...............................................................
11.4 Asymptotic Properties of the PCs................................................. 11.5 Normalized Principal ComponentsAnalysis................................ 11.6 Principal Components as a FactorialMethod............................. 11.7 Common Principal Components................................................... 299 300 303 307 310 313 315 320
x Contents 11.8 Boston Housing............................................................................. 11.9 More Examples............................................................................... 11.10 Exercises........................................................................................ References.................................................................................................... 323 326 335 336 12 Factor Analysis............................................................................................ 12.1 The Orthogonal Factor Model...................................................... 12.2 Estimation of the Factor Model................................................... 12.3 Factor Scores and Strategies................................................... 12.4 Boston Housing............................................................................. 12.5 Exercises......................................................................................... References.................................................................................................... 337 338 345 352 355 358 361 13 Cluster Analysis............ ............................................................................ 13.1 The Problem.................................................................................... 13.2 The Proximity Between Objects................................................. . 13.3 Cluster Algorithms........................................................................ 13.4 Adaptive Weights
Clustering........................................................ 13.5 Spectral Clustering......... ............................................................... 13.6 Boston Housing............................................................................. 13.7 Exercises......................................................................................... References.................................................................................................... 363 364 365 370 381 385 388 391 393 14 Discriminant Analysis............................................................................... 14.1 Allocation Rules for Known Distributions................................. 14.2 Discrimination Rules in Practice................................................. 14.3 Boston Housing............................................................................. 14.4 Exercises......................................................................................... References.................................................................................................... 395 395 402 408 410 411 15 Correspondence Analysis........................................................................ 15.1 Motivation...................................................................................... 15.2 Chi-Square Decomposition.......................................................... 15.3 Correspondence Analysis in Practice.......................................... 15.4 Exercises......................................................................................... 413
413 416 420 429 16 Canonical Correlation Analysis............................................................... 16.1 Most Interesting Linear Combination.......................................... 16.2 Canonical Correlation in Practice................................................. 16.3 Exercises......................................................................................... References.................................................................................................... 431 431 436 441 442 17 Multidimensional Scaling......................................................................... 443 17.1 The Problem.................................................................................... 443 17.2 Metric Multidimensional Scaling................................................. 447
Contents xi 17.3 Nonmetric Multidimensional Scaling.......................................... 452 17.4 Exercises........................................................................................ 458 References................................................................................................... 459 18 Conjoint Measurement Analysis............................................................ 18.1 Introduction................................................................................... 18.2 Design of Data Generation .......................................................... 18.3 Estimation of Preference Orderings............................................ 18.4 Exercises........................................................................................ References .................................................................................................... 461 461 463 465 472 473 19 Applications in Finance............................................................................ 19.1 Portfolio Choice............................................................................. 19.2 Efficient Portfolio.......................................................................... 19.3 Efficient Portfolios in Practice..................................................... 19.4 The Capital Asset Pricing Model (CAPM)................................. 19.5 Exercises........................................................................................
Reference...................................................................................................... 475 475 476 483 484 486 486 20 487 488 491 496 504 519 534 538 539 Computationally IntensiveTechniques.................................................. 20.1 Simplicial Depth............................................................................ 20.2 Projection Pursuit.......................................................................... 20.3 Sliced Inverse Regression............................................................ 20.4 Support Vector Machines............................................................ 20.5 Classification and RegressionTrees............................................. 20.6 Boston Housing............................................................................. 20.7 Exercises........................................................................................ References................................................................................................... Part IV Appendix 21 Symbols and Notations............................................................................ 543 21.1 Basics ............................................................................................. 543 21.2 Mathematical Abbreviations.......................................................... 543 21.3 Samples.......................................................................... ......... . 544 21.4 Densities and Distribution Functions.......................................... 544 21.5
Moments........................................................................................ 544 21.6 Empirical Moments........................................................................ 545 21.7 Distributions................................................................................... 545 22 Data............................................................................................................. 22.1 Boston Housing Data................................................................... 22.2 Swiss Bank Notes.......................................................................... 22.3 Car Data........................................................................................... 547 547 547 548
Contents xii 22.4 Classic Blue Pullovers Data.......................................................... 22.5 U.S. Companies Data.................................................................... 22.6 French Food Data........................................................................... 22.7 Car Marks...................................................................................... 22.8 U.S. Crime Data............................................................................. 22.9 Bankruptcy Data 1........................................................................... 22.10 Bankruptcy Data П........................................................................ 22.11 Journaux Data............................................................................ 22.12 Timebudget Data............................................................................. 22.13 Vocabulary Data............................................................................. 22.14 French Baccalauréat Frequencies................................................. References.................................................................................................... Index 548 549 549 549 549 550 551 551 551 552 553 553 555
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| author | Härdle, Wolfgang 1953- Simar, Léopold |
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| discipline | Mathematik Wirtschaftswissenschaften |
| edition | Fifth edition |
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| isbn | 9783030260057 |
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| spelling | Härdle, Wolfgang 1953- Verfasser (DE-588)110357116 aut Applied multivariate statistical analysis Wolfgang Karl Härdle, Léopold Simar Fifth edition Cham Springer [2019] © 2019 xii, 558 Seiten Illustrationen, Diagramme (teilweise farbig) 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Wirtschaftstheorie (DE-588)4079351-5 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Multivariate Analyse (DE-588)4040708-1 s Statistik (DE-588)4056995-0 s Wirtschaftstheorie (DE-588)4079351-5 s DE-604 Simar, Léopold Verfasser (DE-588)123344107 aut Erscheint auch als Online-Ausgabe 978-3-030-26006-4 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=031817350&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Härdle, Wolfgang 1953- Simar, Léopold Applied multivariate statistical analysis Wirtschaftstheorie (DE-588)4079351-5 gnd Multivariate Analyse (DE-588)4040708-1 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4079351-5 (DE-588)4040708-1 (DE-588)4056995-0 (DE-588)4123623-3 |
| title | Applied multivariate statistical analysis |
| title_auth | Applied multivariate statistical analysis |
| title_exact_search | Applied multivariate statistical analysis |
| title_full | Applied multivariate statistical analysis Wolfgang Karl Härdle, Léopold Simar |
| title_fullStr | Applied multivariate statistical analysis Wolfgang Karl Härdle, Léopold Simar |
| title_full_unstemmed | Applied multivariate statistical analysis Wolfgang Karl Härdle, Léopold Simar |
| title_short | Applied multivariate statistical analysis |
| title_sort | applied multivariate statistical analysis |
| topic | Wirtschaftstheorie (DE-588)4079351-5 gnd Multivariate Analyse (DE-588)4040708-1 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Wirtschaftstheorie Multivariate Analyse Statistik Lehrbuch |
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