rDynMix

This function fits a dynamic mixture by Approximate Maximum Likelihood and by standard maximum likelihood.
Currently only implemented for the lognormal - generalized Pareto case,
with Cauchy or exponential weight.

dynamic

mixture;

simulation.

Estimation of a dynamic lognormal - Generalized Pareto mixture via the Approximate Maximum Likelihood and the Cross-Entropy methods. See Bee, M. (2023) <doi:10.1016/j.csda.2023.107764>.

Marco Bee

FitDynMix

Estimation of Dynamic Mixtures

rDynMix function

<dl><dt>nreps</dt>
<dd>integer: number of observations sampled from the mixture.</dd>
<dt>x</dt>
<dd>numerical vector: if weight = 'cau', values of \(mu_c\), \(\tau\), \(\mu\),
\(\sigma\), \(\xi\), \(\beta\); if weight = 'exp', values of \(\lambda\), \(\mu\), \(\sigma\), \(\xi\), \(\beta\).</dd>
<dt>weight</dt>
<dd>'cau' or 'exp': name of weight distribution.</dd></dl>

Arguments

Simulating a dynamic lognormal-Pareto mixture — rDynMix

<dl>

<dt>nreps</dt>
<dd>integer: number of observations sampled from the mixture.</dd>


<dt>x</dt>
<dd>numerical vector: if weight = 'cau', values of \(mu_c\), \(\tau\), \(\mu\),
\(\sigma\), \(\xi\), \(\beta\); if weight = 'exp', values of \(\lambda\), \(\mu\), \(\sigma\), \(\xi\), \(\beta\).</dd>


<dt>weight</dt>
<dd>'cau' or 'exp': name of weight distribution.</dd>

</dl>

rDynMix: Simulating a dynamic lognormal-Pareto mixture

Description

Usage

Value

Arguments

Details

References

Examples