build_mcculloch_interpolators

Constructs nearest-neighbor interpolation functions for alpha and beta
based on quantile ratios (v_alpha, v_beta) from the lookup table.

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

build_mcculloch_interpolators function

<dl><dt>table</dt>
<dd>Lookup table generated by generate_mcculloch_table.</dd></dl>

Arguments

Build interpolation functions from McCulloch table — build_mcculloch_interpolators

<dl>

<dt>table</dt>
<dd>Lookup table generated by generate_mcculloch_table.</dd>

</dl>

build_mcculloch_interpolators: Build interpolation functions from McCulloch table

Description

Usage

Value

Arguments