Changelog
Source:NEWS.md
moire 3.5.0
New Features
- Implemented maximum runtime functionality (#34)
- The user can now specify a maximum runtime for the MCMC. After the maximum runtime is reached, the MCMC will stop and the current state of the MCMC will be returned.
- Enabled by setting
max_runtime = {time in minutes}
inrun_mcmc()
Other Changes
Modified data loading to ungroup input data when loading long form (#37)
Updated citation and manuscript information
Added OpenMP detection utility
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Implement logging of individual sample log likelihoods
- May be useful for diagnosing issues with particular samples, such as those that come from different populations
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
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calculate_med_allele_freqs()
calculates median allele frequencies -
plot_chain_swaps()
creates diagnostic plots for chain swaps when using parallel tempering
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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 2.0.0
- 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