Description

nwfscDeltaGLM

• Is an R package for implementing a Bayesian stratified delta-GLMM for use when standardizing fishery-independent index data for U.S. West Coast surveys.
• Has built in diagnostic functions and model-comparison tools
• Is intended to improve analysis speed, replicability, peer-review, and interpretation of index standardization methods

Instructions

First, please install JAGS (Just Another Gibbs Sampler) here: http://mcmc-jags.sourceforge.net/

Next, please use R version >=3.1.1 and install the package:

# Install package
install.packages("devtools")
library("devtools")
install_github("nwfsc-assess/nwfscDeltaGLM", ref="1.0.0") # This should reflect the latest formal release
# Load package
library(nwfscDeltaGLM) 

Please see examples folder (i.e., https://github.com/nwfsc-assess/nwfscDeltaGLM/blob/master/examples/Example_delta-GLMM.R) for an example of how to run the model.

Known installation/usage issues

Please read the following list of known problems and solutions

• Users sometimes have trouble loading the package, with R throwing an error about package "rjags". Please reinstall the latest version of JAGS and then re-install nwfscDeltaGLM

Further reading

The user manual (which may not include all current features) can found here: https://github.com/nwfsc-assess/nwfscDeltaGLM/blob/master/examples/bayesGLM_Writeup_2.15.docx

For more details regarding development and testing of this delta-GLMM software please see:

• Shelton, A. O., J. T. Thorson, E. J. Ward, and B. E. Feist. in press. Spatial, semi-parametric models improve estimates of species abundance and distribution. Canadian Journal of Fisheries and Aquatic Sciences.
• Thorson, J. T., and E. J. Ward. 2014. Accounting for vessel effects when standardizing catch rates from cooperative surveys. Fisheries Research 155:168–176.
• Thorson, J. T., and E. Ward. 2013. Accounting for space-time interactions in index standardization models. Fisheries Research 147:426–433.
• Thorson, J. T., I. J. Stewart, and A. E. Punt. 2012. Development and application of an agent-based model to evaluate methods for estimating relative abundance indices for shoaling fish such as Pacific rockfish (Sebastes spp.). ICES Journal of Marine Science 69:635–647.
• Thorson, J. T., I. Stewart, and A. Punt. 2011. Accounting for fish shoals in single- and multi-species survey data using mixture distribution models. Canadian Journal of Fisheries and Aquatic Sciences 68:1681–1693.
• Helser, T. E., A. E. Punt, and R. D. Methot. 2004. A generalized linear mixed model analysis of a multi-vessel fishery resource survey. Fisheries Research 70:251–264.