Extending the linear model with R : generalized linear, mixed effects and nonparametric regression models /: generalized linear, mixed effects and nonparametric regression models. (2016)

• Record Type: Book
• Further Information: Note: Julian J. Faraway.
• Authors: Faraway, Julian James
• Contents: Introduction Binary Response ; Heart Disease Example; Logistic Regression; Inference; Diagnostics; Model Selection; Goodness of Fit; Estimation Problems Binomial and Proportion Responses ; Binomial Regression Model; Inference; Pearson’s χ 2 Statistic; Overdispersion; Quasi-Binomial; Beta Regression Variations on Logistic Regression ; Latent Variables; Link Functions; Prospective and Retrospective Sampling; Prediction and Effective Doses; Matched Case-Control Studies Count Regression ; Poisson Regression; Dispersed Poisson Model; Rate Models; Negative Binomial; Zero Inflated Count Models Contingency Tables; Two-by-Two Tables; Larger Two-Way Tables; Correspondence Analysis; Matched Pairs; Three-Way Contingency Tables; Ordinal Variables Multinomial Data ; Multinomial Logit Model; Linear Discriminant Analysis; Hierarchical or Nested Responses; Ordinal Multinomial Responses Generalized Linear Models ; GLM Definition; Fitting a GLM; Hypothesis Tests; GLM Diagnostics; Sandwich Estimation; Robust Estimation Other GLMs ; Gamma GLM; Inverse Gaussian GLM; Joint Modeling of the Mean and Dispersion; Quasi-Likelihood GLM; Tweedie GLM Random Effects ; Estimation; Inference; Estimating Random Effects; Prediction; Diagnostics; Blocks as Random Effects; Split Plots; Nested Effects; Crossed Effects; Multilevel Models Repeated Measures and Longitudinal Data ; Longitudinal Data; Repeated Measures; Multiple Response Multilevel Models Bayesian Mixed Effect Models ; STAN; INLA; Discussion Mixed Effect Models for Nonnormal Responses ; Generalized Linear Mixed Models; Inference; Binary Response; Count Response; Generalized Estimating Equations Nonparametric Regression ; Kernel Estimators; Splines; Local Polynomials; Confidence Bands; Wavelets; Discussion of Methods; Multivariate Predictors Additive Models; Modeling Ozone Concentration; Additive Models Using mgcv; Generalized Additive Models; Alternating Conditional Expectations; Additivity and Variance Stabilization; Generalized Additive Mixed Models; Multivariate Adaptive Regression Splines Trees; Regression Trees; Tree Pruning; Random Forests; Classification Trees; Classification Using Forests Neural Networks; Statistical Models as NNs; Feed-Forward Neural Network with One Hidden Layer; NN Application; Conclusion Appendix A: Likelihood Theory ; Appendix B: About R Bibliography Index
• Edition: Second edition
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2016
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 519.538; Analysis of variance; Regression analysis; R (Computer program language) -- Mathematical models
• Languages: English
• ISBNs: 9781498720991
• Related ISBNs: 9781498721004; 9781498720984
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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