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Using pdist() in the PST package, two probabilistic suffix trees (PSTs) can be compared to each other. The function will output a value for the degree of divergence between two fitted PSTs. However, how can this value be tested for statistical significance, to see whether it comes from a population where the value is greater than 0?

library(TraMineR)
library(PST)

a <- seqdef("A-A-A-B-B-C")
b <- seqdef("C-C-C-B-B-A")

a_pst <- pstree(a, ymin = 0.001, lik = FALSE, with.missing = FALSE)
b_pst <- pstree(b, ymin = 0.001, lik = FALSE, with.missing = FALSE)

pdist(a_pst, b_pst, l = 10, ns = 1000, symetric = TRUE, output = "mean")

Would it be sufficient to do:

output <- pdist(a_pst, b_pst, l = 10, ns = 1000, symetric = TRUE, output = "all")
t.test(output)

?

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    $\begingroup$ you have introduced new tags pst and vlmc. Can you please add tag wikis? $\endgroup$
    – kjetil b halvorsen ♦
    Aug 6, 2017 at 19:46
  • $\begingroup$ @kjetilbhalvorsen done--we can delete these comments now. $\endgroup$
    – histelheim
    Aug 9, 2017 at 17:26

1 Answer 1

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A t-test is probably not appropriate because the divergence can only be positive.

You may find a statistical test for the divergence between two PST models in Christine Largeron (2003).

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