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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;NaN
s should not occur in find_MAP()
for
D_matrix <- diag(ncol(S)) * d
when
1000 < d < 1e300
;NaN
s 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.