-
Improved Initialization
- The initial adjacency matrix now takes
start_adj
(the maximum likelihood solution) as the starting point to avoid inefficient sampling.
- The initial adjacency matrix now takes
-
Adaptive Sampling
- The sampling of
zeros
andnonzeros
is now adapted to the newly accepted adjacency matrix (adj_s
) rather than the staticstart_adj
.
- The sampling of
-
Efficiency Enhancements
- Skip updates on rejection since the graph remains unchanged.
- Use
find_ids(adj_mat)
instead offind_ids(start_adj)
to ensure edge modifications are correctly tracked after acceptance.
- Example in bggm_missing.R reintroduced; Was removed due to irreproducible CRAN error.
- Addressed CRAN check error when building vignettes (removed example in bggm_missing.R -- will put it back once it's accepted to CRAN).
- Downgraded required R version to 4.0.0
- Replaced dprecated armadillo function
conv_to<>::from
withas_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, atsigma_sd
= 0.5, resulting in delta = 3.prior_sd
is now limited to range 0 -- sqrt(1/2)
- The prior_sd (or rho_sd in var_estimate() ) is limited to ranges between 0 and sqrt(1/8). These values ensure that delta does not go below 1.
- Critical: select() did not return partial correlations, but Fisher-z values in summary(). Fisher values are transformed back to correlation metric. This fixes #90, see changes.
- Upgraded deprecated ggplot guides() argument
- Resolved non positive definite initialization matrix in wishrnd() in copula models when NA's are present in observed variables (fixes #89). See changes here
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