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0 (hodnocen0 x )

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BK

Boca Raton : Chapman & Hall/CRC, 2006

ix, 301 s. : il. ; 25 cm

ISBN 1-58488-424-X (váz.)

Texts in statistical science

Obsahuje bibliografii na s. 289-295 a rejstřík

000024866

Preface v // I Introduction 1 // 2 Binomial Data 25 // 2.1 Challenger Disaster Example 25 // 2.2 Binomial Regression Model 26 // 2.3 Inference 29 // 2.4 Tolerance Distribution 31 // 2.5 Interpreting Odds 31 // 2.6 Prospective and Retrospective Sampling 34 // 2.7 Choice of Link Function 36 // 2.8 Estimation Problems 38 // 2.9 Goodness of Fit 40 // 2.10 Prediction and Effective Doses 41 // 2.11 Overdispersion 43 // 2.12 Matched Case-Control Studies 48 // 3 Count Regression 55 // 3.1 Poisson Regression 55 // 3.2 Rate Models 61 // 3.3 Negative Binomial • 63 // 4 Contingency Tables 69 // 4.1 Two-by-Two Tables 69 // 4.2 Larger Two-Way Tables 75 // 4.3 Matched Pairs 79 // 4.4 Three-Way Contingency Tables 81 // 4.5 Ordinal Variables 88 // 5 Multinomial Data 97 // 5.1 Multinomial Logit Model 97 // 5.2 Hierarchical or Nested Responses 103 // 5.3 Ordinal Multinomial Responses 106 // 6 Generalized Linear Models // 6.1 GLM Definition // 6.2 Fitting a GLM // 6.3 Hypothesis Tests // 6.4 GLM Diagnostics // 7 Other GLMs // 7.1 Gamma GLM // 7.2 Inverse Gaussian GLM // 7.3 Joint Modeling of the Mean and Dispersion // 7.4 Quasi-Likelihood // 8 Random Effects // 8.1 Estimation // 8.2 Inference // 8.3 Predicting Random Effects // 8.4 Blocks as Random Effects // 8.5 Split Plots // 8.6 Nested Effects // 8.7 Crossed Effects // 8.8 Multilevel Models // 9 Repeated Measures and Longitudinal Data // 9.1 Longitudinal Data // 9.2 Repeated Measures // 9.3 Multiple Response Multilevel Models // 10 Mixed Effect Models for Nonnormal Responses // 10.1 Generalized Linear Mixed Models // 10.2 Generalized Estimating Equations // 11 Nonparametric Regression // 11.1 Kernel Estimators // 11.2 Splines // 11.3 Local Polynomials // 11.4 Wavelets // 11.5 Other Methods // 11.6 Comparison of Methods // 11.7 Multivariate Predictors // 12 Additive Models // 12.1 Additive Models Using the gam Package //

12.2 Additive Models Using mgcv // 12.3 Generalized Additive Models // 12.4 Alternating Conditional Expectations // 12.5 Additivity and Variance Stabilization 244 // 12.6 Generalized Additive Mixed Models 246 // 12.7 Multivariate Adaptive Regression Splines 247 // 13 Trees 253 // 13.1 Regression Trees 253 // 13.2 Tree Pruning 257 // 13.3 Classification Trees 261 // 14 Neural Networks 269 // 14.1 Statistical Models as NNs 270 // 14.2 Feed-Forward Neural Network with One Hidden Layer 270 // 14.3 NN Application 272 // 14.4 Conclusion 276 // A Likelihood Theory 279 // A.I Maximum Likelihood 279 // A.2 Hypothesis Testing 282 // B R Information 287 // Bibliography 289 // Index 297