國立高雄大學圖資館 |

Language: English

Back

A parametric approach to nonparametr...

Alvo, Mayer.

A parametric approach to nonparametric statistics

Record Type:	Electronic resources : Monograph/item
Title/Author:	A parametric approach to nonparametric statisticsby Mayer Alvo, Philip L. H. Yu.
Author:	Alvo, Mayer.
other author:	Yu, Philip L. H.
Published:	Cham :Springer International Publishing :2018.
Description:	xiv, 279 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Nonparametric statistics.
Online resource:	https://doi.org/10.1007/978-3-319-94153-0
ISBN:	9783319941530$q(electronic bk.)

A parametric approach to nonparametric statistics
Alvo, Mayer.

A parametric approach to nonparametric statistics[electronic resource] /by Mayer Alvo, Philip L. H. Yu. - Cham :Springer International Publishing :2018. - xiv, 279 p. :ill., digital ;24 cm. - Springer series in the data sciences,2365-5674. - Springer series in the data sciences..

I. Introduction and Fundamentals -- Introduction -- Fundamental Concepts in Parametric Inference -- II. Modern Nonparametric Statistical Methods -- Smooth Goodness of Fit Tests -- One-Sample and Two-Sample Problems -- Multi-Sample Problems -- Tests for Trend and Association -- Optimal Rank Tests -- Efficiency -- III. Selected Applications -- Multiple Change-Point Problems -- Bayesian Models for Ranking Data -- Analysis of Censored Data -- A. Description of Data Sets.

This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter. This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.

ISBN: 9783319941530$q(electronic bk.)

Standard No.: 10.1007/978-3-319-94153-0doiSubjects--Topical Terms:

182700
Nonparametric statistics.

LC Class. No.: QA278.8 / .A486 2018

Dewey Class. No.: 519.54

A parametric approach to nonparametric statistics
LDR:02288nmm a2200349 a 4500 001 545825
003 DE-He213
005 20190326172112.0
006 m d
007 cr nn 008maaau
008 190530s2018 gw s 0 eng d
020 $a 9783319941530$q(electronic bk.)
020 $a 9783319941523$q(paper)
024 7 $a 10.1007/978-3-319-94153-0 $2 doi
035 $a 978-3-319-94153-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA278.8 $b .A486 2018
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a PBWL $2 thema
082 0 4 $a 519.54 $2 23
090 $a QA278.8 $b .A476 2018
100 1 $a Alvo, Mayer. $3 700237
245 1 2 $a A parametric approach to nonparametric statistics $h [electronic resource] / $c by Mayer Alvo, Philip L. H. Yu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xiv, 279 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer series in the data sciences, $x 2365-5674
505 0 $a I. Introduction and Fundamentals -- Introduction -- Fundamental Concepts in Parametric Inference -- II. Modern Nonparametric Statistical Methods -- Smooth Goodness of Fit Tests -- One-Sample and Two-Sample Problems -- Multi-Sample Problems -- Tests for Trend and Association -- Optimal Rank Tests -- Efficiency -- III. Selected Applications -- Multiple Change-Point Problems -- Bayesian Models for Ranking Data -- Analysis of Censored Data -- A. Description of Data Sets.
520 $a This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond and make use of Bayesian methods to analyze ranking data. The book bridges the gap between parametric and nonparametric statistics and presents the best practices of the former while enjoying the robustness properties of the latter. This book can be used in a graduate course in nonparametrics, with parts being accessible to senior undergraduates. In addition, the book will be of wide interest to statisticians and researchers in applied fields.
650 0 $a Nonparametric statistics. $3 182700
650 1 4 $a Probability Theory and Stochastic Processes. $3 274061
650 2 4 $a Statistical Theory and Methods. $3 274054
700 1 $a Yu, Philip L. H. $3 824917
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer series in the data sciences. $3 732743
856 4 0 $u https://doi.org/10.1007/978-3-319-94153-0
950 $a Mathematics and Statistics (Springer-11649)