predict.fitdists {ssdtools} | R Documentation |
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,
proportion = 1:99/100,
average = TRUE,
ci = FALSE,
level = 0.95,
nboot = 1000,
min_pboot = 0.95,
multi_est = TRUE,
ci_method = "weighted_samples",
parametric = TRUE,
delta = 9.21,
control = NULL,
...
)
Arguments
object |
The object. |
percent |
A numeric vector of percent values to estimate hazard concentrations for. Deprecated for |
proportion |
A numeric vector of proportion values to estimate hazard concentrations for. |
average |
A flag specifying whether to provide model averaged values as opposed to a value for each distribution. |
ci |
A flag specifying whether to estimate confidence intervals (by bootstrapping). |
level |
A number between 0 and 1 of the confidence level of the interval. |
nboot |
A count of the number of bootstrap samples to use to estimate the confidence limits. A value of 10,000 is recommended for official guidelines. |
min_pboot |
A number between 0 and 1 of the minimum proportion of bootstrap samples that must successfully fit (return a likelihood) to report the confidence intervals. |
multi_est |
A flag specifying whether to treat the distributions as constituting a single distribution (as opposed to taking the mean) when calculating model averaged estimates. |
ci_method |
A string specifying which method to use for estimating the bootstrap values. Possible values are "multi_free" and "multi_fixed" which treat the distributions as constituting a single distribution but differ in whether the model weights are fixed and "weighted_samples" and "weighted_arithmetic" take bootstrap samples from each distribution proportional to its weight versus calculating the weighted arithmetic means of the lower and upper confidence limits. |
parametric |
A flag specifying whether to perform parametric bootstrapping as opposed to non-parametrically resampling the original data with replacement. |
delta |
A non-negative number specifying the maximum absolute AIC difference cutoff. Distributions with an absolute AIC difference greater than delta are excluded from the calculations. |
control |
A list of control parameters passed to |
... |
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)