Search Results - subject:"Expectation–maximization"

A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation

Hoogerheide, Lennart; Opschoor, Anne; van Dijk, Herman K. - 2012

multimodality and skewness. The basic method makes use of sequences of importance weighted Expectation Maximization steps in order … between target and mixture is minimized. We label this approach Mixture of t by Importance Sampling and Expectation … Maximization (MitISEM). The constructed mixture is used as a candidate density for quick and reliable application of either …

Persistent link: https://www.econbiz.de/10010326223

The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation

Basturk, Nalan; Hoogerheide, Lennart; Opschoor, Anne; … - 2012

This paper presents the R package MitISEM, which provides an automatic and flexible method to approximate a non-elliptical target density using adaptive mixtures of Student-t densities, where only a kernel of the target density is required. The approximation can be used as a candidate density in...

Persistent link: https://www.econbiz.de/10010326521

A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation

Hoogerheide, Lennart; Opschoor, Anne; Dijk, Herman K. van - Tinbergen Instituut - 2012

. The basic method makes use of sequences of importance weighted Expectation Maximization steps in order to efficiently … minimized. We label this approach <I>Mixture of t by Importance Sampling and Expectation Maximization</I> (MitISEM). The …

Persistent link: https://www.econbiz.de/10011257036

Multilevel Mixture with Known Mixing Proportions: Applications to School and Individual Level Overweight and Obesity Data from Birmingham, England

Hussain, Shakir; Shukur, Ghazi - Handelns Utredningsinstitut (HUI Research) - 2012

mixing proportions estimated by parametric Expectation Maximization (EM) of the outcome and the random component from the ML …

Persistent link: https://www.econbiz.de/10010818923

The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation

Basturk, Nalan; Hoogerheide, Lennart; Opschoor, Anne; … - Tinbergen Instituut - 2012

Persistent link: https://www.econbiz.de/10011255807

A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation

Hoogerheide, Lennart; Opschoor, Anne; Dijk, Herman K. van - 2012

Persistent link: https://www.econbiz.de/10009722688

The r package MitISEM : mixture of student-t distributions using importance sampling weighted expectation maximization for efficient and robust simulation

Basturk, Nalan; Hoogerheide, Lennart; Opschoor, Anne; … - 2012

Persistent link: https://www.econbiz.de/10009722972

Fitting nonparametric mixed logit models via expectation-maximization algorithm

Pacifico, Daniele - In: Stata Journal 12 (2012) 2, pp. 284-298

In this article, I provide an illustrative, step-by-step implementation of the expectation-maximization algorithm for …

Persistent link: https://www.econbiz.de/10011002432

Heterogeneity in loss aversion: evidence from field elicitations

Sproul, Thomas; Michaud, Clayton P. - In: Agricultural Finance Review 77 (2017) 1, pp. 196-216

expectation maximization algorithm. Applied results are simulated for investment allocations under myopic loss aversion. Findings …

Persistent link: https://www.econbiz.de/10014667454

Heterogeneity in loss aversion : evidence from field elicitations

Sproul, Thomas; Michaud, Clayton P. - In: Agricultural finance review 77 (2017) 1, pp. 196-216

Persistent link: https://www.econbiz.de/10011700285