plot_fit_vs_true_methods

Plots the true mixture density and compares it with two estimated densities
obtained from different methods (e.g., MLE vs ECF).

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

plot_fit_vs_true_methods function

<dl><dt>data</dt>
<dd>Numeric vector of observations.</dd>
<dt>true_params</dt>
<dd>List of true mixture components.</dd>
<dt>method1</dt>
<dd>First estimation method ("MLE", "ECF", etc.).</dd>
<dt>method2</dt>
<dd>Second estimation method.</dd>
<dt>bins</dt>
<dd>Number of histogram bins.</dd></dl>

Arguments

Compare estimated mixture densities from two methods against the true density — plot_fit_vs_true_methods

<dl>

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


<dt>true_params</dt>
<dd>List of true mixture components.</dd>


<dt>method1</dt>
<dd>First estimation method ("MLE", "ECF", etc.).</dd>


<dt>method2</dt>
<dd>Second estimation method.</dd>


<dt>bins</dt>
<dd>Number of histogram bins.</dd>

</dl>

plot_fit_vs_true_methods: Compare estimated mixture densities from two methods against the true density

Description

Usage

Value

Arguments