check.mono: Check that a detection function is monotone
In mrds: Mark-Recapture Distance Sampling

check.mono

R Documentation

Check that a detection function is monotone

Description

Check that a fitted detection function is monotone non-increasing.

Usage

check.mono(
  df,
  strict = TRUE,
  n.pts = 100,
  tolerance = 1e-06,
  plot = FALSE,
  max.plots = 6
)

Arguments

`df`	a fitted detection function object
`strict`	if `TRUE` (default) the detection function must be "strictly" monotone, that is that (`g(x[i])<=g(x[i-1])`) over the whole range (left to right truncation points).
`n.pts`	number of equally-spaced points between left and right truncation at which to evaluate the detection function (default 100)
`tolerance`	numerical tolerance for monotonicity checks (default 1e-6)
`plot`	plot a diagnostic highlighting the non-monotonic areas (default `FALSE`)
`max.plots`	when `plot=TRUE`, what is the maximum number of plots of non-monotone covariate combinations that should be plotted? Plotted combinations are a random sample of the non-monotonic subset of evaluations. No effect for non-covariate models.

Details

Evaluates a series of points over the range of the detection function (left to right truncation) then determines:

1. If the detection function is always less than or equal to its value at the left truncation (g(x)<=g(left), or usually g(x)<=g(0)). 2. (Optionally) The detection function is always monotone decreasing (g(x[i])<=g(x[i-1])). This check is only performed when strict=TRUE (the default). 3. The detection function is never less than 0 (g(x)>=0). 4. The detection function is never greater than 1 (g(x)<=1).

For models with covariates in the scale parameter of the detection function is evaluated at all observed covariate combinations.

Currently covariates in the shape parameter are not supported.