Index.Summary: Summarize results of a standardized relative abundance index

In ballengerj/FishyR: Functions to Facilitate Standard Analyses Conducted in Fisheries Science

Summarize results of a standardized relative abundance index

Description

Index.Summary

Usage

Index.Summary(
  Y,
  X,
  grid,
  models,
  model.name = c("Poisson", "NB", "ZIP", "ZINB", "Nominal")
)

Arguments

Y	numeric vector representing response variable. In the case of a relative abundance index, this would represent your CPUE measure
X	numeric vector representing the primary covariate of interest. As such, this is the variable you are wanting to get a predicted "effect" for over a range of values this variable can take.
grid	prediction grid. This most commonly would be created via a call to Index.Grid if used in a relative abundance index development question
models	character vector of named models for which you want to get an index summary for
model.name	character vector defining model type. All values of the character vector must take one of five defined values: Poisson identifies use of a "Poisson GLM" for the development of the model NB identifies use of a "Negative Binomial GLM" for the development of the model ZIP identifies use of a "Zero-Inflated Poisson GLM" for the development of the model ZINB identifies use of a "Zero-Inflated Negative Binomial GLM" for the development of the model Nominal identifies the calculation of a nominal index

Value

list the same length as models that contains summary statistics for each model explored

See Also

Other Model Evaluation: Index.Grid(), disp()

ballengerj/FishyR documentation built on June 17, 2022, 10:33 p.m.