Comparison of Multisample Tests of Normality

P. Kosik and K. Sarkadi
Additional contact information
P. Kosik: Hungarian Academy of Sciences, Mathematical Institute
K. Sarkadi: Hungarian Academy of Sciences, Mathematical Institute

A chapter in Probability and Statistical Inference, 1982, pp 183-190 from Springer

Abstract: Abstract Three methods of assessing normality on base of a number of small samples have been compared by Monte Carlo method. The three methods are due to Wilk and Shapiro [8], Durbin [1] and one of the present authors [5], respectively. The power of the tests was evaluated at the alternatives of uniform, exponential, double exponential (Laplace) and Cauchy distributions, in cases r=10, n=4 and r=4, n=10 (r is the number of samples and n is the sample size). Our method turns out to be superior in power in most of the situations considered.

Keywords: Common Distribution; Empirical Comparison; Cauchy Distribution; Empirical Power; Double Exponential (search for similar items in EconPapers)
Date: 1982
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-94-009-7840-9_17

Ordering information: This item can be ordered from
http://www.springer.com/9789400978409

DOI: 10.1007/978-94-009-7840-9_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().