R package with advanced diagnostics to evaluate a Stock Synthesis model. Diagnostics include residual analyses, hindcasting and cross-validation techniques, and retrospective analyses.
To address issue #22 I've updated the User Guidelines handbook to reflect the example model simple included in the package. I also added in the remaining cookbook recipes (R0 profiling, jitter analysis, aspm).
As part of the example data set, I added the posterior distributions from an MCMC run of the simple model. This is included in the data.R file and loaded as data("mcmcSimple"). If this is file is too large, we can remove it.
To address issue #22 I've updated the User Guidelines handbook to reflect the example model
simpleincluded in the package. I also added in the remaining cookbook recipes (R0 profiling, jitter analysis, aspm). As part of the example data set, I added the posterior distributions from an MCMC run of the simple model. This is included in the data.R file and loaded as data("mcmcSimple"). If this is file is too large, we can remove it.