chisqouttest

% Chi-squared test for outlier
% 
% Description:
% 
%      Performs a chisquared test for detection of one outlier in a
%      vector.
% 
% Usage:
% 
%      [pval,chisq] = chisqouttest(x,variance,opposite)
% 
% Arguments:
% 
%        x: a numeric vector of data values. 
% 
% variance: known variance of population. if not given, estimator from
%           sample is taken, but there is not so much sense in such test
%           (it is similar to z-scores) 
% 
% opposite: a logical indicating whether you want to check not the value
%           with  largest difference from the mean, but opposite (lowest,
%           if most suspicious is highest etc.)
% 
% Details:
% 
%      This function performs a simple test for one outlier, based on
%      chisquared distribution of squared differences between data and
%      sample mean. It assumes known variance of population.  It is
%      rather not recommended today for routine use, because several more
%      powerful  tests are implemented (see other functions mentioned
%      below).  It was discussed by Dixon (1950) for the first time, as
%      one of the tests taken into account by him.
% 
% Value:
% 
% chisq: the value of chisquared-statistic.
% 
%  pval: the p-value for the test.
% 
% Note:
% 
%      This test is known to reject only extreme outliers, if no known
%      variance is specified.
% 
% Author(s):
% 
%      Lukasz Komsta, ported from R package 'outliers'.
%    See R News, 6(2):10-13, May 2006
% 
% References:
% 
%      Dixon, W.J. (1950). Analysis of extreme values. Ann. Math. Stat.
%      21, 4, 488-506.
% 
%