init.glme.gev11

Internal function that generates initial parameter sets
(mu0, sigma0, xi) for multi-start optimization in the GEV11 model.
Uses stationary L-moment estimates and random perturbations.

internal

Provides generalized L-moments estimation methods for the
generalized extreme value ('GEV') distribution. Implements both stationary
'GEV' and non-stationary 'GEV11' models where location and scale parameters
vary with time. Includes various penalty functions ('Martins'-'Stedinger',
Park, Cannon, 'Coles'-Dixon) for shape parameter regularization.
Also provides model averaging estimation ('ma.gev') that combines MLE and
L-moment methods with multiple weighting schemes for robust high quantile
estimation. The 'GLME' methodology is described in Shin et al. (2025a)
<doi:10.48550/arXiv.2512.20385>. The non-stationary L-moment method
is based on Shin et al. (2025b) <doi:10.1007/s42952-025-00325-3>.
The model averaging method is described in Shin et al. (2026)
<doi:10.1007/s00477-025-03167-x>.
See also 'Hosking' (1990) <doi:10.1111/j.2517-6161.1990.tb01775.x> for
L-moments theory and 'Martins' and 'Stedinger' (2000)
<doi:10.1029/1999WR900330> for penalized likelihood methods.

Yonggwan Shin

GLmom

Generalized L-Moments Estimation for Extreme Value Distributions

Seokkap Ko

Jihong Park

Yire Shin

Jeong-Soo Park

init.glme.gev11 function

<dl><dt>data</dt>
<dd>Numeric vector of data.</dd>
<dt>ntry</dt>
<dd>Number of initial parameter sets to generate. Default is 10.</dd>
<dt>pretheta</dt>
<dd>Pre-estimated parameter vector (mu0, mu1, sigma0, sigma1, xi).</dd></dl>

Arguments

Initialize parameters for multi-start GEV11 optimization — init.glme.gev11

<dl>

<dt>data</dt>
<dd>Numeric vector of data.</dd>


<dt>ntry</dt>
<dd>Number of initial parameter sets to generate. Default is 10.</dd>


<dt>pretheta</dt>
<dd>Pre-estimated parameter vector (mu0, mu1, sigma0, sigma1, xi).</dd>

</dl>

init.glme.gev11: Initialize parameters for multi-start GEV11 optimization

Description

Usage

Value

Arguments