A wrapper on ssd_hc() that by default calculates
all hazard concentrations from 1 to 99%.
# S3 method for 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,
...
)The object.
A numeric vector of percentages.
A flag specifying whether to estimate confidence intervals (by parametric bootstrapping).
A number between 0 and 1 of the confidence level.
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.
A flag specifying whether to model average the estimates.
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.
A number of the minimum proportion of bootstrap samples that must successfully fit in the sense of returning a likelihood.
A flag specifying whether to perform parametric as opposed to non-parametric bootstrapping.
A list of control parameters passed to stats::optim().
Unused.
It is useful for plotting purposes.
ssd_hc() and ssd_plot()
fits <- ssd_fit_dists(ssddata::ccme_boron)
predict(fits)
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