Electronic Resource

Essential statistical inference : theory and methods

---

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.
Dennis 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. ​

---

Ketersediaan

Informasi Detail

Judul Seri

Springer texts in statistics

No. Panggil

E476

Penerbit

New York : Springer., 2013

Deskripsi Fisik

xvii, 568 hlm.

Bahasa

English

ISBN/ISSN

9781461448181

Klasifikasi

NONE

Tipe Isi

text

Tipe Media

computer

Tipe Pembawa

online resource

Edisi

1

Subjek

Matematika Statistika

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Dennis D Boos, L. A Stefanski

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar