Changelog

Source: NEWS.md

gips 1.3.0

Multi-sample support

gips() now accepts a list of covariance matrices and a vector of sample sizes, enabling Bayesian model selection with a shared permutation symmetry across G independent groups:

g <- gips(list(S1, S2, S3), c(n1, n2, n3))
g_MAP <- find_MAP(g, optimizer = "BF")

Each group has its own covariance matrix Sigma_g and can have its own prior hyperparameters D_matrix_g and delta_g, but all share the same symmetry group Gamma. The MLE exists when min(n_g) >= n0. All existing single-sample usage is fully unchanged.

gips 1.2.4

Performance gain

project_matrix() is now implemented in C++ internally. Additionally, several internal calculations used by log_posteriori_of_gips() and find_MAP(optimizer = "BF") were optimized.

For Brute Force optimization:

permutation size	6	7	8	9	10
v1.2.3	1.26 s	4.06 s	30.19 s	4.35 min	1 h 46 min
v1.2.4	0.52 s	1.89 s	10.34 s	1.21 min	12.14 min

For log_posteriori_of_gips() evaluated on 1000 random permutations of a given size:

permutation size	30	50	100	200	300
v1.2.3	2.31 s	2.31 s	11.70 s	46.49 s	110.17 s
v1.2.4	0.84 s	1.26 s	3.24 s	15.73 s	39.47 s

The above tables are based on the code from Pull Request #99.

Update to functions

• find_MAP() now uses its precomputed cyclic-subgroup generators for optimizer = "BF" through perm_size = 10; Brute Force is the default through this size.
• Added caching for find_MAP(optimizer = "MH") to store computed values. This reduces computation time for the Markov chain, particularly when the acceptance rate is low.
• Improved find_MAP(optimizer = "MH") with a forced move mechanism: when the cache is full (all neighbors have been evaluated), the algorithm now makes a probabilistic move based on the cached values instead of exiting early, which improves exploration of the permutation space. See #115.
• plot.gips() now uses ggplot2 for all plot types.
• plot.gips(type = "all", "best", "both", or "n0") is now much faster for large iteration counts.
• project_matrix(): The precomputed_equal_indices parameter is no longer used and will be removed in v1.4.0.

Bugfixes:

• Documentation improvements: grammar and style corrections in roxygen comments, vignettes, and error messages.
• plot.gips(type = "n0") works properly after multiple optimizations. See #114.

gips 1.2.3

CRAN release: 2025-03-18

Performance gain

There was a significant speed improvement in get_structure_constants(), which is used internally by posterior calculations. For 1000 random permutations of a given size:

permutation size	30	50	100	200	300
v1.2.2	0.09 s	0.10 s	0.25 s	~10 s	~25 s
v1.2.3	0.07 s	0.08 s	0.10 s	0.17 s	~0.20 s

This change consequently improved log_posteriori_of_gips(). For 1000 random permutations of a given size:

permutation size	30	50	100	200	300
v1.2.2	1.50 s	2.49 s	7.08 s	55.25 s	169.77 s
v1.2.3	1.29 s	2.24 s	6.84 s	31.73 s	85.10 s

Update to functions

• 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.

gips 1.2.2

Bugfixes:

• logLik.gips() will return an object of class logLik;
• Better Vignettes titles.

gips 1.2.1

CRAN release: 2023-08-12

Bugfix:

• One test on alternative BLAS/LAPACK has an alternative check for a singular matrix. Found by CRAN’s ATLAS test.

gips 1.2.0

CRAN release: 2023-08-07

New functions

• BIC.gips()
• AIC.gips()
• logLik.gips()
• as.character.gips()

Update to functions

• 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;
• Everywhere a permutation was expected, the 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.

Bugfixes:

• Sometimes, 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;
• When 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;
• Slightly different punctuation in print.gips();
• Tremendous vignettes and documentation improvements;
• Proper testing of examples;
• 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;
• Absurdly long structure constants vectors may overflow an 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).

gips 1.0.0

CRAN release: 2022-10-13

• This is the first release of gips.