search
Functionstart_adj
(the
maximum likelihood solution) as the starting point to avoid inefficient
sampling.zeros
and nonzeros
is now
adapted to the newly accepted adjacency matrix
(adj_s
) rather than the static start_adj
.find_ids(adj_mat)
instead of
find_ids(start_adj)
to ensure edge modifications are
correctly tracked after acceptance.conv_to<>::from
with as_scalar
prior_sd
: Adjusted computation of delta. Also, changed
default value for estimation: sqrt(1/3) resulting in delta = 2. For
model testing default is more tight, at sigma_sd
= 0.5,
resulting in delta = 3.prior_sd
is now limited to range 0 – sqrt(1/2)BFpack dependency error fixed.
This version of BGGM included changes based on the JOSS reviews: see here for the overview and here for specific issues.
BGGM was almost completely rewritten for version
2.0.0
. This was due to adding support for binary, ordinal,
and mixed data, which required that the methods be written in
c ++
. Unfortunately, as a result, lots of code from version
1.0.0
is broken.
Full support for binary, ordinal, and mixed data. This is
implemented with the argument type
roll_your_own
: compute custom network statistics
from a weighted adjacency matrix or a partial correlation
matrix
pcor_to_cor
: convert the sampled partial correlation
matrices into correlation matrices.
zero_order_cors
: compute zero order
correlations
convergence
: acf and trace plots
posterior_samples
: extract posterior
samples
regression_summary
: summarize multivariate
regression
pcor_sum
: Compute and compare partial correlation
sums
weighted_adj_mat
: Extract the Weighted Adjacency
Matrix
pcor_mat
: Extract the Partial Correlation
Matrix
Five additional data sets were added.
ggm_compare_ppc
: added option for custom network
statistics
Added option to control for variables with
formula
A progress bar was added to many functions
Initial CRAN release