predict.fitdists: Predict Hazard Concentrations of fitdists Object

In ssdtools: Species Sensitivity Distributions

Predict Hazard Concentrations of fitdists Object

Description

A wrapper on ssd_hc() that by default calculates all hazard concentrations from 1 to 99%.

Usage

## S3 method for class 'fitdists'
predict(
  object,
  percent = 1:99,
  ci = FALSE,
  level = 0.95,
  nboot = 1000,
  average = TRUE,
  delta = 7,
  min_pboot = 0.99,
  parametric = TRUE,
  control = NULL,
  ...
)

Arguments

object	The object.
percent	A numeric vector of percentages.
ci	A flag specifying whether to estimate confidence intervals (by parametric bootstrapping).
level	A number between 0 and 1 of the confidence level.
nboot	A count of the number of bootstrap samples to use to estimate the se and confidence limits. A value of 10000 is recommended for official guidelines.
average	A flag specifying whether to model average the estimates.
delta	A non-negative number specifying the maximum absolute Akaike Information-theoretic Criterion difference cutoff. Distributions with an absolute difference from the best model greater than the cutoff are excluded.
min_pboot	A number of the minimum proportion of bootstrap samples that must successfully fit in the sense of returning a likelihood.
parametric	A flag specifying whether to perform parametric as opposed to non-parametric bootstrapping.
control	A list of control parameters passed to stats::optim().
...	Unused.

Details

It is useful for plotting purposes.

See Also

ssd_hc() and ssd_plot()

Examples

fits <- ssd_fit_dists(ssddata::ccme_boron)
predict(fits)

ssdtools documentation built on Sept. 8, 2023, 5:56 p.m.