MitISEM-package: Mixture of Student t Distributions using Importance Sampling...

In MitISEM: Mixture of Student t Distributions using Importance Sampling and Expectation Maximization

Description

Approximates a univariate or multivariate density using mixture of Student t distributions, achieved by Importance Sampling and Expectation Maximization algorithms

Details

Package:	MitISEM
Type:	Package
Version:	1.2
Date:	2017-07-10
License:	GPL (>= 3)

Flexible multivariate function approximation using adapted Mixture of Student t Distributions. Mixture of t distribution is obtained using Importance Sampling weighted Expectation Maximization algorithm.

Author(s)

N. Basturk, L.F. Hoogerheide, A. Opschoor, H.K. van Dijk

Maintainer: N. Basturk

References

Basturk, N., Grassi, S., Hoogerheide, L., Opschoor, A. and Van Dijk, H. K. (2017) The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference. Journal of Statistical Software, 79(1): 1-39. doi: 10.18637/jss.v079.i01.

Hoogerheide L., Opschoor, A. and Van Dijk, H. K. (2012) A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation. Journal of Econometrics, 171(2): 101-120. http://www.sciencedirect.com/science/article/pii/S0304407612001583.

MitISEM documentation built on May 2, 2019, 1:57 p.m.