https://github.com/pbs-assess/larkin

Fit and forecast from Larkin and Ricker stock-recruitment models
https://github.com/pbs-assess/larkin

Last synced: 2 months ago
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Fit and forecast from Larkin and Ricker stock-recruitment models

• Host: GitHub
• URL: https://github.com/pbs-assess/larkin
• Owner: pbs-assess
• License: gpl-3.0
• Created: 2021-05-27T22:43:02.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-06-04T17:51:01.000Z (7 months ago)
• Last Synced: 2024-06-05T03:07:02.483Z (7 months ago)
• Language: R
• Homepage:
• Size: 715 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# larkin

Forecast from Larkin and Ricker stock-recruitment models

[![R-CMD-check](https://github.com/luke-a-rogers/larkin/workflows/R-CMD-check/badge.svg)](https://github.com/luke-a-rogers/larkin/actions)

[![Project Status: WIP – Initial development is in progress, but there

has not yet been a stable, usable release suitable for the

public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)

## Installation

1. Install the R package `cmdstanr` (see ).

``` r

install.packages("cmdstanr", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))

```

2. Install CmdStan (see ).

``` r

cmdstanr::check_cmdstan_toolchain()

cmdstanr::install_cmdstan(cores = parallel::detectCores())

```

3. Install `larkin`.

``` r

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