Consider the following MWE, where I try to pass starting values to FindDistributionParameters[]:

emptyμ[n_] := Table[Subscript[μf, i], {i, 1, n}];
emptyΣ[n_] := 
  Table[Subscript[σf^(1 + KroneckerDelta[i, j]), 
    Sort[{i, j}]], {i, 1, n}, {j, 1, n}];
fit = FindDistributionParameters[data, 
    emptyΣ[n], ν]];

I tried to add starting values to FindDistributionParameters[] as:

p = Flatten[{emptyμ[n], emptyΣ[n], ν}]
p0 = Flatten[{Mean[data], Covariance[data], 5}]
start1 = {p, p0}\[Transpose]
start2 = Rule @@@ %
start3 = {emptyμ[n] -> Mean[data], emptyΣ[n] -> Covariance[data] , ν -> 5}

fit = FindDistributionParameters[data, 
    emptyΣ[n], ν], start1(*start2, start3*)];

However, nothing works.

Also, is it possible to pass only starting values for one of the required parameters, e.g. start4 = {{ν, 5}}?

  • $\begingroup$ Hm weird. I strongly believe that this is a bug. I would appreciate it if you contacted Wolfram Support about it. $\endgroup$ – Henrik Schumacher Nov 4 '18 at 15:45
  • $\begingroup$ Have you got an evaluation order problem? Would wrapping Evaluate round MultivariateTDistribution[...] help? $\endgroup$ – mikado Nov 4 '18 at 16:02
  • $\begingroup$ Thank you @HenrikSchumacher, I just opened a Question in Wolfram's community forum - unfortunately I do not have access to their advanced technical support. $\endgroup$ – CFW Nov 4 '18 at 16:02
  • $\begingroup$ @mikado, just tried - no joy. $\endgroup$ – CFW Nov 4 '18 at 16:04
  • $\begingroup$ What does "nothing works" mean? Is there a specific error message? $\endgroup$ – JimB Nov 5 '18 at 0:19

Edit: I've removed my answer about blaming the problem on using Subscript (although I think that one should avoid subscripts almost always).

I'm now pretty sure the issue is that the covariance term is listed twice in the starting values:

start1 = {p, p0}\[Transpose]

Duplicate starting values

This is fixed with

start1 = DeleteDuplicates[{p, p0}\[Transpose]]

But sometimes the maximum number of iterations might need increasing. Also, it might be best to create a table of log likelihood values keeping ν as an integer and choose the integer value that maximizes the log of the likelihood.


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