New upper bounds for tight and fast approximation of Fisher's exact test in dependency rule mining
type: Item
instance of: scholarly article
title: New upper bounds for tight and fast approximation of Fisher's exact test in dependency rule mining
zbMATH Open document ID: 1468.62072
author: Wilhelmiina Hämäläinen
published in: Computational Statistics and Data Analysis
publication date: 2018-08-15T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62H17
zbMATH DE Number: 6918718
zbMATH Keywords: Fisher's exact test
zbMATH Keywords: \(p\)-value
zbMATH Keywords: hypergeometric distribution
zbMATH Keywords: upper bound
zbMATH Keywords: approximation
zbMATH Keywords: dependency rule
zbMATH Keywords: data mining
describes a project that uses: UCI-ml
describes a project that uses: gprof
MaRDI profile type: Publication
full work available at URL: j.csda.2015.08.002
OpenAlex ID: W1160788859
cites work: A survey of exact inference for contingency tables. With comments and a rejoinder by the author
cites work: Comparing the asymptotic power of exact tests in \(2\times 2\) tables
cites work: Efficient search methods for statistical dependency rules
cites work: A network algorithm for the exact treatment of the 2×k contingency table
cites work: A Network Algorithm for Performing Fisher's Exact Test in r × c Contingency Tables
cites work: A major improvement to the network algorithm for Fisher's exact test in \(2\times c\) contingency tables
cites work: A survey of algorithms for exact distributions of test statistics in r\(\times c\) contingency tables with fixed margins
cites work: An accurate computation of the hypergeometric distribution function
DOI: 10.1016/J.CSDA.2015.08.002
description: scientific article; zbMATH DE number 6918718