dcmgnd

This function estimates the marginal density for univariate constrained
mixture of generalized normal distribution (CMGND) models.

The 'cmgnd' implements the constrained mixture of generalized normal distributions model, a flexible statistical framework for modelling univariate data exhibiting non-normal features such as skewness, multi-modality, and heavy tails. By imposing constraints on model parameters, the 'cmgnd' reduces estimation complexity while maintaining high descriptive power, offering an efficient solution in the presence of distributional irregularities. For more details see Duttilo and Gattone (2025) <doi:10.1007/s00180-025-01638-x> and Duttilo et al (2025) <doi:10.48550/arXiv.2506.03285>.

Pierdomenico Duttilo

cmgnd

Constrained Mixture of Generalized Normal Distributions

Stefano Antonio Gattone

Alfred Kume

dcmgnd function

<dl><dt>x</dt>
<dd>A numeric vector representing the observed data points.</dd>
<dt>parameters</dt>
<dd>A matrix or data.frame containing the parameters of the CMGND model.
This can also be an object returned from the `cmgnd()` function, representing a previously estimated CMGND model.</dd></dl>

Arguments

Marginal Density Estimation for CMGND Models — dcmgnd

<dl>

<dt>x</dt>
<dd>A numeric vector representing the observed data points.</dd>


<dt>parameters</dt>
<dd>A matrix or data.frame containing the parameters of the CMGND model.
This can also be an object returned from the `cmgnd()` function, representing a previously estimated CMGND model.</dd>

</dl>

dcmgnd: Marginal Density Estimation for CMGND Models

Description

Usage

Value

Arguments

Details

See Also