NEWS

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moire 3.3.2

Minor bugfix that corrects an issue with temperature gradient tuning when using parallel tempering.

moire 3.3.1

Minor bugfix that corrects an issue with parameter logging when not using parallel tempering.

moire 3.3.0

This is a minor revision that greatly improves the speed of the MCMC computationally, various bug fixes, and improvements to numerical stability when starting the MCMC.

moire 3.2.0

This is a minor revision that fixes bugs in the adaptive temperature gradient approach and changes the default priors on false positive and false negative rates.

• New default priors
• Fixed bug in adaptive temperature gradient approach
• Numerical stability improvements
• New summarization functions
  • calculate_med_allele_freqs() calculates median allele frequencies
  • plot_chain_swaps() creates diagnostic plots for chain swaps when using parallel tempering

moire 3.1.0

This is a minor revision that introduces new functionality to improve mixing of the MCMC. This also updates the required version of R to 4.0.0. and C++ to C++17.

• Added option to specify prior on within-host relatedness
• Added adaptive approach to tune temperature gradient used during parallel tempering
• Various bugfixes and improvements

moire 3.0.0

This is a major revision to moire, introducing a simplified API and functionality to infer within host relatedness and effective MOI. This release also introduces a parallel tempering based approach that leverages OpenMP, greatly improving mixing of the MCMC.

moire 2.2.0

• Added support for running multiple chains simultaneously, then pooling output
• fix bug with missing data
• various other bugfixes and improvements

moire 2.1.0

• Implemented a new error model that removes sensitivity to total number of alleles at a locus
• Removed option to marginalize out latent genotypes below some complexity threshold
• bug fixes, documentation improvements

moire 2.0.1

• Minor bugfix when sampling that caused computational slow down

moire 2.0.0

• Underlying model no longer uses pseudo marginal MH algorithm. Instead, model is augmented with latent genotypes above some user defined complexity level which are then sampled. Loci below the user defined complexity level have the latent state fully marginalized out.
• Removed dependency on GSL
• various bugfixes and speedups

moire 1.1.1

• fixed overflow bug that would dramatically increase computational costs
• fixed bug in sampling complexity of infection where accepted updates weren't being recorded in some cases

moire 1.1.0

• Added several new common functions for analyzing data
• Added functions to import data in common formats to the format required
• Made errors an independent parameter across samples
• Changed error model to no longer depend on underlying number of strains contributing alleles
• Removed multiple chain implementations. If multiple chains are desired, use multiprocessing
• Added progress bar for duration of MCMC

moire 1.0.0

• Initial release of moire.