Kstest: Difference between revisions

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===Synopsis===
===Synopsis===
:vals = kstest(x,distname)
:vals = kstest(x,distname)
INPUTS:
====INPUTS====
* x = matrix (column vector) in which the sample data is stored.
* '''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'.  
'''distname''' = string, optional distribution name to assume as the parent distribution for the sample. Default value is 'normal'.  
OUTPUTS:
====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.
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.
* '''Ks''' =  value of the adjusted test statistic.
* Dn = unadjusted test statistic.
* '''Dn''' = unadjusted test statistic.
* parameters = maximum likelihood estimates.
* '''parameters''' = maximum likelihood estimates.
===Examples===
===Examples===
kstest(x)
kstest(x)

Revision as of 19:56, 2 September 2008

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

CHITEST, DISTFIT