pbs-assess/stockseasonr: Seasonal Predictions of Stock Composition and Abundance

An integrated model for estimating seasonal changes in abundance and stock composition. Designed and tested using fisheries data, estimates of total abundance assume a negative binomial distribution while composition estimates assume a Dirichlet-multinomial. stockseasonr is intended to generate predictions of composition and group-specific abundance. Group-specific abundance is calculated as the product of predicted total abundance and the probability of encountering a given group. It borrows significant functionality from glmmTMB and sdmTMB. Smooth terms can be incorporated using `s()` notation from mgcv and random intercepts following the familiar lme4 syntax. The full model is fit in TMB. Also includes basic plotting functions.

install.packages("remotes")
remotes::install_github("pbs-assess/stockseasonr")