Generalised Smirnov two-sample homogeneity tests - Maple Application Center
Application Center Applications Generalised Smirnov two-sample homogeneity tests

Generalised Smirnov two-sample homogeneity tests

Author
: Dr. Melvin Brown
Engineering software solutions from Maplesoft
This Application runs in Maple. Don't have Maple? No problem!
 Try Maple free for 15 days!

The problem addressed by this worksheet is:  Given two samples of data, which may contain ties, how may one test the hypothesis that they are drawn from the same distribution?

The worksheet demonstrates the use of a MAPLE implementation of an algorithm to perform two-sample homogeneity tests, based on any one of three Kolmogorov-Smirnov (K-S) test statistics.

The MAPLE package KSNstat, which is introduced in this worksheet, contains the MAPLE procedure gsmirn which implements the GSMIRN algorithm given in 1994 by Nikiforov [1] to calculate exact p-values for generalised (conditionally distribution-free) two-sample homogeneity tests based on two-sided and one-sided Kolomogorov-Smirnov statistics.  Notably, the Nikiforov algorithm covers the range from discrete to continuous distributions; specifically, it handles tied data points.

[1] Exact Smirnov two-sample tests for arbitrary distributions, A. Nikiforov, Appl.Stat., vol.43, No. 1. pp.265-270, 1994. 

Application Details

Publish Date: July 06, 2011
Created In: Maple 15
Language: English

More Like This

Interactive Country Data Explorer
Multivariate Distributions In Maple
ランダムウォーク
The Advanced Encryption Standard and its modes of operation
Decision Analysis using Bayes Rule
Regression and Data Fitting in Maple
Time Series Analysis: Forecasting Average Global Temperatures