plot.bayesmanecfit {bayesnec}R Documentation

plot.bayesmanecfit

Description

Generates a plot of a fitted bayesmanecfit object, as returned by bnec.

Usage

## S3 method for class 'bayesmanecfit'
plot(
  x,
  ...,
  CI = TRUE,
  add_nec = TRUE,
  position_legend = "topright",
  add_ec10 = FALSE,
  xform = NA,
  lxform = NA,
  force_x = FALSE,
  jitter_x = FALSE,
  jitter_y = FALSE,
  ylab = "Response",
  xlab = "Predictor",
  xticks = NA,
  all_models = FALSE
)

Arguments

x

An object of class bayesnecfit as returned by bnec.

...

Additional arguments to plot.

CI

A logical value indicating if credibility intervals on the model fit should be plotted, calculated as the upper and lower bounds of the individual predicted values from all posterior samples.

add_nec

A logical value indicating if the estimated NEC value and 95% credible intervals should be added to the plot.

position_legend

A numeric vector indicating the location of the NEC or EC10 legend, as per a call to legend.

add_ec10

A logical value indicating if an estimated EC10 value and 95% credible intervals should be added to the plot.

xform

A function to be applied as a transformation of the x data.

lxform

A function to be applied as a transformation only to axis labels and the annotated NEC / EC10 values.

force_x

A logical value indicating if the argument xform should be forced on the predictor values. This is useful when the user transforms the predictor beforehand (e.g. when using a non-standard base function).

jitter_x

A logical value indicating if the x data points on the plot should be jittered.

jitter_y

A logical value indicating if the y data points on the plot should be jittered.

ylab

A character vector to use for the y-axis label.

xlab

A character vector to use for the x-axis label.

xticks

A numeric vector indicate where to place the tick marks of the x-axis.

all_models

A logical value indicating if all models in the model set should be plotted simultaneously, or if a model average plot should be returned.

Value

a plot of the fitted model


[Package bayesnec version 2.0.2 Index]