README.md

In DanielReedOcean/ACCASPR: For Fitting Generalised Additive Models to Fish Stock Metrics

ACCASPR

ACCASPR provides several helper functions for linking fish stock metrics (e.g., condition, abundance, recruitment) to indices of pelagic habitat quality using gams. The basic workflow for using these functions is outlined below.

Installation

You can install ACCASPR from github with:

# install.packages("devtools")
devtools::install_github("DanielReedOcean/ACCASPR")

Workflow

The basic workflow for using ACCASPR is as follows:

1. Tidy data sets then determine predictors & response variable
2. Run all possible GAMs with run_gams
3. Remove models with excessive concurvity with filter_gams
4. Rank models according to AIC with rank_gams
5. View top models in table format with tabulate_gams
6. Plot effects of each predictor on a model with plot_gam_effect
7. Plot time series data, model fit, confidence intervals, & contribution of each predictor with plot_gam_ts
8. Examine residuals, autocorrelation, & quantiles with examine_gam_res

DanielReedOcean/ACCASPR documentation built on Aug. 22, 2019, 3:34 a.m.