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NEWS

1. Improved Initialization
   • The initial adjacency matrix now takes start_adj (the maximum likelihood solution) as the starting point to avoid inefficient sampling.
2. Adaptive Sampling
   • The sampling of zeros and nonzeros is now adapted to the newly accepted adjacency matrix (adj_s) rather than the static start_adj.
3. Efficiency Enhancements
   • Skip updates on rejection since the graph remains unchanged.
     
   • Use find_ids(adj_mat) instead of find_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 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)

• 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

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