mcculloch_lookup_estimate

Estimates alpha and beta using quantile ratios and interpolation functions.
Gamma and delta are derived directly from quantiles.

Provides various functions for parameter estimation of one-dimensional
stable distributions and their mixtures. It implements a diverse set of
estimation methods, including quantile-based approaches, regression methods
based on the empirical characteristic function (empirical, kernel, and
recursive), and maximum likelihood estimation. For mixture models, it provides
stochastic expectation–maximization (SEM) algorithms and Bayesian estimation
methods using sampling and importance sampling to overcome the long burn-in
period of Markov Chain Monte Carlo (MCMC) strategies. The package also includes
tools and statistical tests for analyzing whether a dataset follows a stable
distribution. Some of the implemented methods are described in
Hajjaji, O., Manou-Abi, S. M., and Slaoui, Y. (2024) <doi:10.1080/02664763.2024.2434627>.

Solym Manou-Abi

MixStable

Parameter Estimation for Stable Distributions and Their Mixtures

Adam Najib

Yousri Slaoui

mcculloch_lookup_estimate function

<dl><dt>X</dt>
<dd>Numeric vector of data.</dd>
<dt>interpolators</dt>
<dd>Optional list with interp_alpha and interp_beta functions.</dd>
<dt>interp_alpha</dt>
<dd>Optional function to interpolate alpha.</dd>
<dt>interp_beta</dt>
<dd>Optional function to interpolate beta.</dd></dl>

Arguments

Estimate stable parameters using McCulloch lookup — mcculloch_lookup_estimate

<dl>

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


<dt>interpolators</dt>
<dd>Optional list with interp_alpha and interp_beta functions.</dd>


<dt>interp_alpha</dt>
<dd>Optional function to interpolate alpha.</dd>


<dt>interp_beta</dt>
<dd>Optional function to interpolate beta.</dd>

</dl>

mcculloch_lookup_estimate: Estimate stable parameters using McCulloch lookup

Description

Usage

Value

Arguments