R package gamair: Data for ”GAMs: An Introduction with R”. Data sets and scripts used in the book ”Generalized Additive Models: An Introduction with R”, Wood (2006) CRC: The aim of this book is to present a comprehensive introduction to linear, generalized linear, generalized additive and mixed models. Moreover, the book contains explanations of the theory underlying the statistical methods and material on statistical modelling in R. The book is written to be accessible and the author used a fairly smooth way even in the case of advanced statistical notions. The book is intended as a text both for the students from the last two years of an undergraduate math/statistics programmme upwards and researchers. The prerequisite is an honest course in probability and statistics. Finally, let us note that the book includes some practical examples illustrating the theory and corresponding exercises. The appendix is devoted to some matrix algebra.

References in zbMATH (referenced in 242 articles )

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  1. Sobotka, Fabian; Kneib, Thomas: Geoadditive expectile regression (2012)
  2. Staicu, Ana-Maria; Crainiceanu, Ciprian M.; Reich, Daniel S.; Ruppert, David: Modeling functional data with spatially heterogeneous shape characteristics (2012)
  3. Stoklosa, Jakub; Huggins, Richard M.: A robust P-spline approach to closed population capture-recapture models with time dependence and heterogeneity (2012)
  4. Tsujitani, Masaaki; Tanaka, Yusuke; Sakon, Masato: Survival data analysis with time-dependent covariates using generalized additive models (2012)
  5. Voulgaraki, Anastasia; Kedem, Benjamin; Graubard, Barry I.: Semiparametric regression in testicular germ cell data (2012)
  6. Wand, M. P.: Book review of: Y. Wang, Smoothing splines. Methods and applications (2012)
  7. Xu, Ganggang; Huang, Jianhua Z.: Asymptotic optimality and efficient computation of the leave-subject-out cross-validation (2012)
  8. Yamada, Yuji: Properties of optimal smooth functions in additive models for hedging multivariate derivatives (2012)
  9. Cai, Bo; Lawson, Andrew B.; McDermott, Suzanne; Aelion, C. Marjorie: Variable selection for spatial latent predictors under Bayesian spatial model (2011)
  10. Gertheiss, Jan; Oehrlein, Franziska: Testing linearity and relevance of ordinal predictors (2011)
  11. Huggins, Richard; Hwang, Wen-Han: A review of the use of conditional likelihood in capture-recapture experiments (2011)
  12. Hwang, Wen-Han; Huggins, Richard: A semiparametric model for a functional behavioural response to capture in capture-recapture experiments (2011)
  13. Koenker, Roger: Additive models for quantile regression: model selection and confidence bands (2011)
  14. Liu, Hai; Chan, Kung-Sik: Generalized additive models for zero-inflated data with partial constraints (2011)
  15. Marra, Giampiero; Radice, Rosalba: A flexible instrumental variable approach (2011)
  16. Marra, Giampiero; Radice, Rosalba: Estimation of a semiparametric recursive bivariate probit model in the presence of endogeneity (2011)
  17. Marra, Giampiero; Wood, Simon N.: Practical variable selection for generalized additive models (2011)
  18. Matteson, David S.; McLean, Mathew W.; Woodard, Dawn B.; Henderson, Shane G.: Forecasting emergency medical service call arrival rates (2011)
  19. Nummi, Tapio; Pan, Jianxin; Siren, Tarja; Liu, Kun: Testing for cubic smoothing splines under dependent data (2011)
  20. Rodríguez-Álvarez, María Xosé; Tahoces, Pablo G.; Cadarso-Suárez, Carmen; Lado, María José: Comparative study of ROC regression techniques -- applications for the computer-aided diagnostic system in breast cancer detection (2011)

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