plot.select_Millar {TropFishR}

Millar's selectivity plot

Description

This function plots the selectivity estimates of Millar's selectivity model (select_Millar).

Usage

## S3 method for class 'select_Millar'
plot(
  x,
  plotlens = NULL,
  standardise = TRUE,
  deviance_plot = TRUE,
  selectivity_plot = TRUE,
  xlab_dev = "Length [cm]",
  xlab_sel = "Length [cm]",
  ylab_dev = "Mesh size [cm]",
  ylab_sel = "Relative retention",
  title_dev = "Deviance residuals",
  title_sel = NULL,
  ...
)

Arguments

x

a list of the class "select_Millar" containing the results of Millar's selectivity model

plotlens

A vector with lengths which should be used for drawing the selection curves

standardise

A parameter indicating if the retention should be realtive to the maximum value (Default: TRUE).

deviance_plot

logical (Default: TRUE); indicating whether a plot of deviance residuals should be displayed

selectivity_plot

logical (Default: TRUE); indicating whether a plot of relative retention selectivities should be displayed

xlab_dev

character string. Label for x axis of deviance plot. Default: "Length [cm]"

xlab_sel

character string. Label for x axis of selectivity plot. Default: "Length [cm]"

ylab_dev

character string. Label for y axis of deviance plot. Default: "Mesh size [cm]"

ylab_sel

character string. Label for y axis of selectivity plot. Default: "Relative retention".

title_dev

character string. Label for main title of deviance plot. Default: "Deviance residuals".

title_sel

character string. Label for main title of selectivity plot. Default is taken from the results of the select_Millar (e.g. res$rtype).

...

additional parameter options from plot function

Details

This function draws a selectivity plot for the object class "select_Millar", which is created by applying Millar's selectivity model select_Millar.

References

Millar, R. B., Holst, R., 1997. Estimation of gillnet and hook selectivity using log-linear models. ICES Journal of Marine Science: Journal du Conseil, 54(3), 471-477.

Examples

data(gillnet)

output <- select_Millar(gillnet, x0 = c(60,4), rel.power = rep(1,8),
   rtype = "norm.loc", plot = FALSE)

plot(output, plotlens = seq(40,90,0.1), deviance_plot = FALSE)