GBTEST

NAME

gbtest - Compute statistical tests on data

SYNOPSIS

gbtest [options] <tests list>

DESCRIPTION

Compute statistical tests on data. Each test is specified by a unique name and optional parameters follows, separated by commas. Depending on the test, one, two or three columns of data are expected. ’1 dist’ tests expect data in [0,1] from a distribution function. ’1 sample’ tests expect a single columns. Test on ’pairs’ expect two columns of equal length. Test on ’2 samples’ expect two columns of data, possibly of different length. Test on 2+ and 3+ samples expect a varying number of columns. If more columns are provided, the test is repeated for any column in the case of 1 sample test, and any couple of columns in the case of 2 sample tests. In the last case, the output is expressed in matrix format, with estimated statistics on the lower triangle and p-scores (if requested) on the upper. The removal of ’nan’ entries is automatic, and is performed consistently with the nature of the test.

Tests typically assume 1, 2 or 3+ samples. Available tests are:
D+,D-,D,V 1 dist

Kolmogorov-Smirnov tests on cumulated data

W2,A2,U2

1 dist Cramer-von Mises tests on cumulated data

CHI2-1

1 samp Chi-Sqrd, 1 samp. 2nd column: th. prob.

	WILCO		1 samp Wilcoxon signed-rank test (mode=0)
	TS		1 samp Student’s T (mean=0)
	TR-TP		1 samp Test of randomness: turning points
	TR-DS		1 samp Test of randomness: difference sign
	TR-RT		1 samp Test of randomness: rank test
	R		pairs Pearson’s correlation coefficient
	RHO		pairs Spearman’s Rho rank correlation
	TAU		pairs Kendall’s Tau correlation

CHI2-2

pairs Chi-Sqrd, 2 samples

TP

pairs Student’s T with paired samples

WILCO2

pairs Wilcoxon test on paired samples

	KS		2 samp Kolmogorov-Smirnov test
	T		2 samp Student’s T with same variances
	TH		2 samp Student’s T with different variances
	F		2 samp F-Test for different variances
	WMW		2 samp Wilcoxon-Mann-Whitney U
	FP		2 samp Fligner-Policello standardized Uˆ

LEV-MEAN

2+ samp Levene equality of variances using means

LEV-MED

2+ samp Levene equality of variances using medians

KW

3+ samp Kruscal-Wallis test on 3+ samples

CHI2-N

3+ samp Multi-columns contingency table analysis

OPTIONS

	-p		compute associated significance
	-s		input data are already sorted in ascending order
	-F		specify the input fields separators (default " \t")
	-o		set the output format (default ’%12.6e’)
	-v		verbosity: 0 none, 1 headings, 2+ description (default 0)
	-h		this help

EXAMPLES

gbtest FP < file

compute the Fligner-Policello test on the columns of ’file’, considering all possible pairings.

gbtest KW -p < file

compute the Kruscal-Wallis test and its p-score on the first three columns of data in ’file’

AUTHOR

Written by Giulio Bottazzi

REPORTING BUGS

Report bugs to <gbutils@googlegroups.com>

Package home page <http://cafim.sssup.it/˜giulio/software/gbutils/index.html>

COPYRIGHT

Copyright © 2001-2018 Giulio Bottazzi This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License (version 2) as published by the Free Software Foundation;

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.