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NEWS
simmr 0.5.1
- Fixed bug introduced in 0.5.0 affecting the prior distribution on the residual standard deviation
- Added extra argument to simmr_mcmc and simmr_mcmc_tdf to enable more control on the prior distribution on the residual standard deviation
simmr 0.5.0
- Implemented new Fixed Form Variational Bayes method for fitting SIMMs (publication forthcoming)
- Added new GGally matrix plots
simmr 0.4.6
- Implemented vdiffr for better checking of output plots
- Added capture.output to remove verbose testing
- Added feature to allow for >2 sources to combined in combine_sources
- Added ability to use data in matrix, data frame, or tibble format without error
- Changed the way prior_viz object is plotted and returned to allow for greater customisation
- Improved test that to test for bad source mean and sd shapes
- Added a new vignette on advanced plotting (and moved other parts out of main vignette)
simmr 0.4.5
- Updated new checkmate error checking for multiple functions
- Added new tests for 90%+ code coverage
- Fixed a bug that stopped some plots being outputted correctly
- Fixed some broken examples
simmr 0.4.4
- Updated the simmr_elicit function to provide a more explicit warning for bad input objects
- Updated compare_sources and compare_groups to allow exporting of the plot object for editing purposes
- Used styler to correct code style
simmr 0.4.3
- Fixed a bug in combine_sources that stopped it working for multiple groups
- Added in a load more tests to increase code coverage
- Implemented checkmate for error checking in simmr_load
simmr 0.4.2
- Fixed a bug with the summary function which was always reporting the same group when an individual group was specified (didnât apply to multiple group summaries). Added a test for that bug.
- Updated posterior_predictive to produce some more helpful output
simmr 0.4.1
- Fixed some major bugs to plot.simmr_output and compare_groups which caused the wrong groups to be selected
- Fixed a minor dependency bug as no longer using coda
simmr 0.4.0
- Included
prior_viz to visualise and contrast the prior and posterior distributions
- Included
posterior_posterior_predictive to visualise model fit using bayesplot
- Added
simmr_mcmc_tdf to estimate trophic discrimination factors for known diet studies
- Updated
simmr_mcmc to use R2jags
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