title: The numerical compearing of classical and permutation methods of statistical hypothesis testing
metadata.name: dc.contributor.author
metadata.value: Melas, Viatcheslav B.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Salnikov, Dmitrii I.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Gudulina, Anastasia O.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2016-09-28T15:54:07Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2016-09-28T15:54:07Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2016-09
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Melas V.B., Salnikov D. I., Gudulina A.O. The numerical compearing of classical and permutation methods of statistical hypothesis testing. Vestnik of Saint Petersburg University. Series 1. Mathematics. Mechanics. Astronomy, 2016, vol. 3 (61), issue 3, pp. 415–423.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: 10.21638/11701/spbu01.2016.309
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/3911
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The article is devoted to the classical problem of a statistical hypothesis test for the equality of two
  distributions. For normal distributions in many ways t-test is the best one. But in practice, compared
  distributions often are not normal ones and, generally speaking, are not known. The non-parametric
  Kolmogorov—Smirnov test is usually used to solve this problem in case when the investigator knows
  nothing about the compared distributions. The article deals with methods based on permutations. In recent
  years such methods have attracted attention by its simplicity, versatility and relatively high efficiency. A
  comparative study of power of a few permutation tests and classical methods (such as Kolmogorov—
  Smirnov test, t-test and Mann—Whitney test) for a wide class of distribution functions was done by using
  stochastic simulation’s methods. Normal and Cauchy distributions and its mixtures are considered as well
  as exponential, Weibull, Fisher and Student’s distributions.
  It was found that for many typical distributions the permutation test, based on the sum of the
  absolute values of the differencesis, is the most powerful one. The advantage of this test over the others
  is considerably greater for the case, when symmetrical distributions with the same centers are compared.
  Thus, the permutation test can be recommended for using in cases where the compared distributions are
  different from normal ones. Refs 9. Tables 5.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: Работа выполнена при поддержке СПбГУ (проект 6.38.435.2015).
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Series 1. Mathematics. Mechanics. Astronomy;Issue 3
metadata.lang: -
metadata.name: dc.subject
metadata.value: statistical hypothesis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: permutation methods
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: The numerical compearing of classical and permutation methods of statistical hypothesis testing
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: Melas.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/3911/1/Melas.pdf
resources.format: Adobe PDF
resources.size: 228,62 kB