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gbtest - Compute statistical tests on data

Author

       Written by Giulio Bottazzi

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 U^

       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

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'

Name

       gbtest - Compute statistical tests on data

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

Reporting Bugs

Synopsis

gbtest [options] <testslist>

See Also