predict.fitburrlioz

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

Species sensitivity distributions are cumulative probability
distributions which are fitted to toxicity concentrations for
different species as described by Posthuma et al.(2001)
<isbn:9781566705783>. The ssdtools package uses Maximum Likelihood to
fit distributions such as the gamma, log-logistic, log-normal and
Weibull to censored and/or weighted data. Multiple distributions can
be averaged using Akaike Information Criteria. Confidence intervals
on hazard concentrations and proportions are produced by parametric
bootstrapping.

Joe Thorley

ssdtools

Species Sensitivity Distributions

Carl Schwarz

Rebecca Fisher

David Fox

Angeline Tillmanns

Ali Azizishirazi

Kathleen McTavish

Heather Thompson

Doug Spry

Rick van Dam

Graham Batley

Andy Teucher

Seb Dalgarno

Emilie Doussantousse

Stephanie Hazlitt

Nadine Hussein

Nan-Hung Hsieh

Sergio Ibarra Espinosa

Province of British Columbia 

Environment and Climate Change Canada 

predict.fitburrlioz function

<dl><dt>object</dt>
<dd>The object.</dd>
<dt>percent</dt>
<dd>A numeric vector of percentages.</dd>
<dt>ci</dt>
<dd>A flag specifying whether to estimate confidence intervals (by parametric bootstrapping).</dd>
<dt>level</dt>
<dd>A number between 0 and 1 of the confidence level.</dd>
<dt>nboot</dt>
<dd>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.</dd>
<dt>min_pboot</dt>
<dd>A number of the minimum proportion of bootstrap samples that must successfully fit
in the sense of returning a likelihood.</dd>
<dt>parametric</dt>
<dd>A flag specifying whether to perform parametric as opposed to non-parametric bootstrapping.</dd>
<dt>...</dt>
<dd>Unused.</dd></dl>

Arguments

Predict Hazard Concentrations of fitburrlioz Object — predict.fitburrlioz

<dl>

<dt>object</dt>
<dd>The object.</dd>


<dt>percent</dt>
<dd>A numeric vector of percentages.</dd>


<dt>ci</dt>
<dd>A flag specifying whether to estimate confidence intervals (by parametric bootstrapping).</dd>


<dt>level</dt>
<dd>A number between 0 and 1 of the confidence level.</dd>


<dt>nboot</dt>
<dd>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.</dd>


<dt>min_pboot</dt>
<dd>A number of the minimum proportion of bootstrap samples that must successfully fit
in the sense of returning a likelihood.</dd>


<dt>parametric</dt>
<dd>A flag specifying whether to perform parametric as opposed to non-parametric bootstrapping.</dd>


<dt>...</dt>
<dd>Unused.</dd>

</dl>

Predict Hazard Concentrations of fitburrlioz Object

predict.fitburrlioz: Predict Hazard Concentrations of fitburrlioz Object

Description

Usage

Arguments

Details

See Also

Examples