PLS_Toolbox Documentation: kstest< kdensity ktool >

kstest

Purpose

Kolmogorov-Smirnov test that a sample has a specified distribution.

Synopsis

 

vals = kstest(x,distname)

INPUTS:

                         x =   matrix (column vector) in which the sample data is stored.

                                 distname = string, optional distribution name to assume as the parent distribution for the sample. Default value is 'normal'.

OUTPUTS:

 

The return value is a structure with fields (larger values indicate rejecting the named distribution as a candidate parent distribution for the sample). The ks is the value of the Kolmogorov-Smirnov statistic and is  times the maximum difference of the distributions. The maximum difference in the distributions is returned as Dn.

 

         Ks =   value of the adjusted test statistic.

         Dn =   unadjusted test statistic.

parameters =   maximum likelihood estimates.

Examples

 

kstest(x)

kstest(x,'exp')

See Also


< kdensity ktool >