rforcpue: rforcpue a set of functions to assist with CPUE...
In haddonm/rforcpue: Functions to Assist With The Analysis of CPUE Data

rforcpue

R Documentation

rforcpue a set of functions to assist with CPUE standardization

Description

The rforcpue package provides numerous functions to assist with the standardization of fisheries CPUE data. There are three types of functions 1) analytical functions that assist with cpue standardizations, 2) plotting functions that can be used to illustrate the results of the standardizations, and 3) utility functions that assist with data manipulations, and other activities that occur when conducting standardizations.

Analytical functions

coef.outce: S3 function applied to the output of standLM
dosingle: conducts a standardization of indat using the inmodel, that can be generated using makeonemodel
geomean: Calculates the bias corrected geometric mean
makecategorical: converts a series of variables in a data.frame into factors
makemodels: Given a list of factors this generates a list of formula for inclusion in glm or standLM
makeonemodel: generates a single model for use in dosingle
scaleCE: Rescales a vector of CPUE to a mean of 1.0 or of avCE
standLM: Uses lm to standardize log-transformed CPUE
summary.outce: an S3 function to summarize a standardization output

Plotting functions

addnorm: fits a normal distribution curve to a given histogram
diagnosticPlot: plots some diagnostic details for a standardization
impactplot: Plots the influence of each factor
inthist: a replacement for the hist function for use with integers
plotdata: plots graphs of untransformed and log-transformed data
plotprep: defines a base graphics window for use in RStudio
plotstand: Plots the optimum model vs the year-only model
plotstandFY: The same as plotstand but for Fishing year species
yearBubble: Generates a bubbleplot of x against Year

Utility functions

addcount: adds a new column to input data.frame that is a count of the number of years in which the identified variable, default 'Vessel' occurs each year for each level of the factor
fishery: generates vectors of year, catch, effort, and cpue
getfact: extracts a given factor from the analysis with its standard errors and rescaled to a mean of 1.0
getStand: extracts the main year paramters from a standLM object with its StErr and confidence itervals
properties: Checks a data.frame for NAs and counts; used for QC
removeEmpty: removes empty strings from a vector of strings
selectdata: simplifies the selection of data from a data.frame by depth, years, zones, method, and fishery
toExcel: copys the selected vector or matrix to the clipboard it can be pasted directly into Excel or other software
yearNA: counts the NAs in each numeric field in a data.frame
yearZero: counts the zeros and NAs in identified fields in a df