mrlplot

An empirical mean residual life plot, including confidence intervals, is produced. The mean residual life plot aids the selection of a threshold for the GPD or point process models.

 htest

 hplot

General functions for performing extreme value analysis. In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes. Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included. For a tutorial, see Gilleland and Katz (2016) <doi: 10.18637/jss.v072.i08> and for bootstrapping, please see Gilleland (2020) <doi: 10.1175/JTECH-D-20-0070.1>.

Eric Gilleland

extRemes

Extreme Value Analysis

mrlplot function

<dl> <dt>x</dt>
<dd>numeric vector of data.</dd> <dt>nint</dt>
<dd>Number of thresholds to use.</dd> <dt>alpha</dt>
<dd>number giving the 1 - <code>alpha</code> confidence levels to use.</dd> <dt>na.action</dt>
<dd>function to be called to handle missing values.</dd> <dt>xlab</dt>
<dd>character string giving the abscissa label to use.</dd>
 
 <dt>...</dt>
<dd>optional arguments to <code>plot</code>.</dd></dl>

Arguments

Author

Mean Residual Life Plot — mrlplot

<dl>

 <dt>x</dt>
<dd>numeric vector of data.</dd>

 <dt>nint</dt>
<dd>Number of thresholds to use.</dd>

 <dt>alpha</dt>
<dd>number giving the 1 - <code>alpha</code> confidence levels to use.</dd>

 <dt>na.action</dt>
<dd>function to be called to handle missing values.</dd>

 <dt>xlab</dt>
<dd>character string giving the abscissa label to use.</dd>
 
 <dt>...</dt>
<dd>optional arguments to <code>plot</code>.</dd>

</dl>

mrlplot: Mean Residual Life Plot

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples