censored_weibull_fit

Finds the optimal left-censoring threshold(s) at which 
the data series should be censored to make sure that the observations 
in the tail are likely sampled from a Weibull distribution

Extreme value analysis with the metastatistical extreme value distribution MEVD (Marani and Ignaccolo, 2015, <doi:10.1016/j.advwatres.2015.03.001>) and some of its variants. In particular, analysis can be performed with the simplified metastatistical extreme value distribution SMEV (Marra et al., 2019, <doi:10.1016/j.advwatres.2019.04.002>) and the temporal metastatistical extreme value distribution TMEV (Falkensteiner et al., 2023, <doi:10.1016/j.wace.2023.100601>). Parameters can be estimated with probability weighted moments, maximum likelihood and least squares. The data can also be left-censored prior to a fit. Density, distribution function, quantile function and random generation for the MEVD, SMEV and TMEV are included. In addition, functions for the calculation of return levels including confidence intervals are provided. For a description of use cases please see the provided references.

Harald Schellander

mevr

Fitting the Metastatistical Extreme Value Distribution MEVD

Alexander Lieb

Marc-Andre Falkensteiner

censored_weibull_fit function

<dl><dt>x</dt>
<dd>A tibble which is most commonly a result of function 
<code>weibull_tail_test</code>.</dd>
<dt>thresholds</dt>
<dd>A numeric or vector of quantiles which shal be tested 
as optimal threshold for left-censoring.</dd></dl>

Arguments

Fit Weibull distribution to censored data — censored_weibull_fit

<dl>

<dt>x</dt>
<dd>A tibble which is most commonly a result of function 
<code>weibull_tail_test</code>.</dd>


<dt>thresholds</dt>
<dd>A numeric or vector of quantiles which shal be tested 
as optimal threshold for left-censoring.</dd>

</dl>

censored_weibull_fit: Fit Weibull distribution to censored data

Description

Usage

Value

Arguments

Examples