public static double GetCriticalValues(MultiCompType ctype, double alpha, int DegreeofFreedom, int ng)
{
//% Get the minimum of the specified critical values
double crit = Double.MaxValue;
double crit1 = Double.MaxValue;
switch (ctype)
{
//case MultiCompType.Tukey_Kramer | MultiCompType.HSD:
// double crit1 = stdrinv(1-alpha, df, ng) / sqrt(2);
// // The T-K algorithm is inaccurate for small alpha, so compute
// // an upper bound for it and make sure it's in range.
// ub = GetCriticalValues(MultiCompType.Dunn_Sidak, alpha, df, ng);
// if (crit1 > ub) crit1 = ub;
// break;
//case MultiCompType.Dunn_Sidak:
// kstar = nchoosek(ng, 2);
// alf = 1-Math.Pow((1-alpha),(1/kstar));
// if (isinf(df))
// crit1 = norminv(1-alf/2);
// else
// crit1 = tinv(1-alf/2, df);
// break;
case MultiCompType.Bonferroni:
double kstar = NChooseK(ng, 2);
if (double.IsInfinity(DegreeofFreedom))
crit1 = normsinv(1 - alpha / (2*kstar));
else
crit1 = tinv(1 - alpha / (2*kstar), DegreeofFreedom);
break;
// case MultiCompType.LSD:
// if (isinf(df))
// crit1 = norminv(1 - alpha / 2);
// else
// crit1 = tinv(1 - alpha / 2, df);
// end
// break;
// case MultiCompType.Scheffe:
// if (isinf(df))
// tmp = chi2inv(1-alpha, ng-1) / (ng-1);
// else
// tmp = finv(1-alpha, ng-1, df);
// end
// crit1 = sqrt((ng-1) * tmp);
// break;
default:
new Exception("Not Implemented Yet");
break;
}
crit = Math.Min(crit, crit1);
return crit;
}
public static void MultipleComparisons(/*comparison,means,h,*/ MultiCompSource Source, double[] GroupMeans, string[] GroupNames,int[] GroupMemberCounts, int DegreesofFreedom, double sqrtMSE, Single alpha, MultiCompType ctype /*, estimate ,dimension*/)
{
if ((alpha<=0) || (alpha>=1))
new Exception("Alpha for Multiple Comparisons analysis should be between 1 and 0");
switch(Source)
{
case MultiCompSource.ANOVA1:
//GroupMemberCounts <- n = stats.n(:);
//sqrtMSE <- s = stats.s;
int ng = GroupMemberCounts.GetLength(0);
if (DegreesofFreedom < 1)
new Exception("stats:multcompare:NotEnoughData Cannot compare means with 0 degrees of freedom for error.");
double crit = GetCriticalValues( ctype, alpha, DegreesofFreedom, ng);
double[] gcov = new double[ng];
for(int i = 0; i<ng; i++) gcov[i] = Math.Pow(sqrtMSE,2)/GroupMemberCounts[i];
break;
case MultiCompSource.ANOVA2:
break;
case MultiCompSource.ANOVAN:
break;
}//Switch
//% Create output matrix showing tests for all pairwise comparisons
//% and graph that approximates these tests.
//[M,MM,hh] = makeM(gmeans, gcov, crit, gnames, mname, dodisp);
//comparison = M;
//if (nargout>1), means = MM; end
//if (nargout>2), h = hh; end
}
