Forecast from Larkin and Ricker stock-recruitment models
cmdstanr
(see https://mc-stan.org/cmdstanr/index.html).install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
cmdstanr::check_cmdstan_toolchain()
cmdstanr::install_cmdstan(cores = parallel::detectCores())
larkin
.remotes::install_github("pbs-assess/larkin")
Changes implemented on 21 July 2023 - forecast no longer includes random error. A single, deterministic forecast is generated for each posterior draw. - timevary input parameter was removed as this is determined by value of prior on omega - the MLE of larkin model was included as an alternative to Bayesian estimation, in forecast() using cmdstanr's optimize() function
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