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There was a significant improvement in the speed of calculation. Details in the table below for 1000 random permutations of a given size:
| permutation size | 30 | 50 | 100 | 200 | 300 |
|---|---|---|---|---|---|
| old computation time | 0.09 s | 0.10 s | 0.25 s | ~10 s | ~25 s |
| new computation time | 0.07 s | 0.08 s | 0.10 s | 0.17 s | ~0.20 s |
plot.gips() can get type = "n0", which
will plot the change of n0 along the “MH” optimization.
Handy for deciding of burn-in time;find_MAP(optimizer = "MH") tracks the n0
along the optimization;summary.gips() calculates Likelihood-Ratio test.logLik.gips() will return an object of class
logLik;BIC.gips()AIC.gips()logLik.gips()as.character.gips()gips() has a new default
D_matrix = mean(diag(S)) * diag(p);summary.gips() calculates AIC,
BIC, and n_parameters (number of free
parameters in the covariance matrix);get_probabilities_from_gips() will return a sorted
vector;compare_posteriories_of_perms() and
compare_log_posteriories_of_perms() have a new parameter
digits;gips object
can now be passed and interpreted as a permutation. Those are:
perm in gips(),
project_matrix(), prepare_orthogonal_matrix(),
get_structure_constants(),
calculate_gamma_function();perm1 and perm2 in
compare_posteriories_of_perms(),
compare_log_posteriories_of_perms();x in gips_perm();plot.gips() can get type = "MLE", which is
an alias for type = "heatmap";find_MAP(optimizer = "BF") is 3 times faster;find_MAP(optimizer = "BF") is default for
perm_size <= 9.post_probabilities underflows to 0. This is
appropriately validated now;NaNs should not occur in find_MAP() for
D_matrix <- diag(ncol(S)) * d when
1000 < d < 1e300;NaNs do occur in find_MAP(), they
will throw an error (used to show a warning);Inf better handled in print.gips();print.*() functions will print \n in the
end;print.gips();delta parameter of gips() has to be bigger
than 1. We used to restrict it to bigger than
2;project_matrix() shows a warning when the
non-positive-semi-definite matrix is passed as an S
argument;project_matrix() preserves colnames() and
rownames() of a matrix;D_matrix is checked for containing any NaN
or Inf values;integer. Now we use double;compare_log_posteriories_of_perms() and
compare_posteriories_of_perms() show an error when given
two incomparable gips objects (with different
parameters).These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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