Essential Statistical Inference: Theory and Methods. Graduate

Essential Statistical Inference: Theory and Methods. Graduate This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems.An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology nnis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods. Autor: Dennis D. Boos, L A Stefanski Wydawnictwo: Springer EN Rok wydania: 2015 Okładka: miękka Liczba stron: 568 Wymiary: 2.35 x 1.55 x 0.34 cm Język: angielski ISBN: 9781489987938