東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Pairwise multiple comparisons = theo...

Shiraishi, Taka-aki.

Linked to FindBook

Google Book

Amazon

博客來

Pairwise multiple comparisons = theory and computation /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pairwise multiple comparisons/ by Taka-aki Shiraishi, Hiroshi Sugiura, Shin-ichi Matsuda.
Reminder of title:	theory and computation /
Author:	Shiraishi, Taka-aki.
other author:	Sugiura, Hiroshi.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	viii, 102 p. :ill., digital ;24 cm.
[NT 15003449]:	1. All-Pairwise Comparisons in Homoscedastic Multi-Sample Models -- 2. Multiple Comparisons in Heteroscedastic Multi-Sample Models -- 3. Multiple Comparison Procedures under Simple Order Restrictions -- 4.: Nonparametric Procedures Based on Rank Statistics -- 5. Comparing the Simulated Power of Multiple Comparison Tests -- 6. Application of Multiple Comparison Tests to Real Data -- 7. Computation of Distribution Functions for Statistics under Simple Ordered Restrictions -- 8. Related Topics -- Index.
Contained By:	Springer eBooks
Subject:	Analysis of variance. -
Online resource:	https://doi.org/10.1007/978-981-15-0066-4
ISBN:	9789811500664

Pairwise multiple comparisons = theory and computation /
Shiraishi, Taka-aki.

Pairwise multiple comparisonstheory and computation /[electronic resource] :by Taka-aki Shiraishi, Hiroshi Sugiura, Shin-ichi Matsuda. - Singapore :Springer Singapore :2019. - viii, 102 p. :ill., digital ;24 cm. - SpringerBriefs in statistics. - SpringerBriefs in statistics..

1. All-Pairwise Comparisons in Homoscedastic Multi-Sample Models -- 2. Multiple Comparisons in Heteroscedastic Multi-Sample Models -- 3. Multiple Comparison Procedures under Simple Order Restrictions -- 4.: Nonparametric Procedures Based on Rank Statistics -- 5. Comparing the Simulated Power of Multiple Comparison Tests -- 6. Application of Multiple Comparison Tests to Real Data -- 7. Computation of Distribution Functions for Statistics under Simple Ordered Restrictions -- 8. Related Topics -- Index.

This book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing closed testing procedures based on maximum absolute values of some two-sample t-test statistics and on F-test statistics in homoscedastic multi-sample models. It shows that (1) the multi-step procedures are more powerful than single-step procedures and the Ryan/Einot-Gabriel/Welsh tests, and (2) the confidence regions induced by the multi-step procedures are equivalent to simultaneous confidence intervals. Next, it describes the multi-step test procedure in heteroscedastic multi-sample models, which is superior to the single-step Games-Howell procedure. In the context of simple ordered restrictions of means, the authors also discuss closed testing procedures based on maximum values of two-sample one-sided t-test statistics and based on Bartholomew's statistics. Furthermore, the book presents distribution-free procedures and describes simulation studies performed under the null hypothesis and some alternative hypotheses. Although single-step multiple comparison procedures are generally used, the closed testing procedures described are more powerful than the single-step procedures. In order to execute the multiple comparison procedures, the upper 100α percentiles of the complicated distributions are required. Classical integral formulas such as Simpson's rule and the Gaussian rule have been used for the calculation of the integral transform that appears in statistical calculations. However, these formulas are not effective for the complicated distribution. As such, the authors introduce the sinc method, which is optimal in terms of accuracy and computational cost.

ISBN: 9789811500664

Standard No.: 10.1007/978-981-15-0066-4doiSubjects--Topical Terms:

516400
Analysis of variance.

LC Class. No.: QA279 / .S557 2019

Dewey Class. No.: 519.538

Pairwise multiple comparisons = theory and computation /
LDR:03255nmm a2200337 a 4500 001 2193341
003 DE-He213
005 20191223144851.0
006 m d
007 cr nn 008maaau
008 200514s2019 si s 0 eng d
020 $a 9789811500664 $q (electronic bk.)
020 $a 9789811500657 $q (paper)
024 7 $a 10.1007/978-981-15-0066-4 $2 doi
035 $a 978-981-15-0066-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA279 $b .S557 2019
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.538 $2 23
090 $a QA279 $b .S558 2019
100 1 $a Shiraishi, Taka-aki. $3 3414454
245 1 0 $a Pairwise multiple comparisons $h [electronic resource] : $b theory and computation / $c by Taka-aki Shiraishi, Hiroshi Sugiura, Shin-ichi Matsuda.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a viii, 102 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics
505 0 $a 1. All-Pairwise Comparisons in Homoscedastic Multi-Sample Models -- 2. Multiple Comparisons in Heteroscedastic Multi-Sample Models -- 3. Multiple Comparison Procedures under Simple Order Restrictions -- 4.: Nonparametric Procedures Based on Rank Statistics -- 5. Comparing the Simulated Power of Multiple Comparison Tests -- 6. Application of Multiple Comparison Tests to Real Data -- 7. Computation of Distribution Functions for Statistics under Simple Ordered Restrictions -- 8. Related Topics -- Index.
520 $a This book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing closed testing procedures based on maximum absolute values of some two-sample t-test statistics and on F-test statistics in homoscedastic multi-sample models. It shows that (1) the multi-step procedures are more powerful than single-step procedures and the Ryan/Einot-Gabriel/Welsh tests, and (2) the confidence regions induced by the multi-step procedures are equivalent to simultaneous confidence intervals. Next, it describes the multi-step test procedure in heteroscedastic multi-sample models, which is superior to the single-step Games-Howell procedure. In the context of simple ordered restrictions of means, the authors also discuss closed testing procedures based on maximum values of two-sample one-sided t-test statistics and based on Bartholomew's statistics. Furthermore, the book presents distribution-free procedures and describes simulation studies performed under the null hypothesis and some alternative hypotheses. Although single-step multiple comparison procedures are generally used, the closed testing procedures described are more powerful than the single-step procedures. In order to execute the multiple comparison procedures, the upper 100α percentiles of the complicated distributions are required. Classical integral formulas such as Simpson's rule and the Gaussian rule have been used for the calculation of the integral transform that appears in statistical calculations. However, these formulas are not effective for the complicated distribution. As such, the authors introduce the sinc method, which is optimal in terms of accuracy and computational cost.
650 0 $a Analysis of variance. $3 516400
650 1 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Applied Statistics. $3 3300946
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 891040
650 2 4 $a Biomedical Engineering/Biotechnology. $3 2162071
700 1 $a Sugiura, Hiroshi. $3 3414455
700 1 $a Matsuda, Shin-ichi. $3 3414456
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in statistics. $3 1565658
856 4 0 $u https://doi.org/10.1007/978-981-15-0066-4
950 $a Mathematics and Statistics (Springer-11649)