Search Results - subject:"expectation maximization"

SV mixture : classification using EM algorithm

Hachicha, Ahmed; Hachicha, Fatma; Masmoudi, Afif - 2013

The present paper presents a theoretical extension of our earlier work entitled“A comparative study of two models SV with MCMC algorithm” cited, Rev Quant Finan Acc (2012) 38:479-493 DOI 10.1007/s11156-011-0236-1 where we propose initially a mixture stochastic volatility model providing a...

Persistent link: https://www.econbiz.de/10009755511

EM algorithm for Markov chains observed via Gaussian noise and point process information: Theory and case studies

Damian, Camilla; Eksi, Zehra; Frey, Rüdiger - In: Statistics & Risk Modeling 35 (2018) 1-2, pp. 51-72

Abstract In this paper we study parameter estimation via the Expectation Maximization (EM) algorithm for a continuous …

Persistent link: https://www.econbiz.de/10014621265

An expectation-maximization algorithm to estimate the parameters of the Markov chain choice model

Şimşek, A. Serdar; Topaloğlu, Hüseyin - In: Operations research 66 (2018) 3, pp. 748-760

Persistent link: https://www.econbiz.de/10011884287

Model-based capacitated clustering with posterior regularization

Mai, Feng; Fry, Michael J.; Ohlmann, Jeffrey W. - In: European journal of operational research : EJOR 271 (2018) 2, pp. 594-605

Persistent link: https://www.econbiz.de/10011890298

Regime-switching model on hourly electricity spot price dynamics

Gyamerah, Samuel Asante; Ngare, Philip - In: Journal of mathematical finance 8 (2018) 1, pp. 102-110

Persistent link: https://www.econbiz.de/10011846143

Learning and optimizing through dynamic pricing

Kumar, Ravi; Li, Ang; Wang, Wei - In: Journal of revenue and pricing management 17 (2018) 2, pp. 63-77

Persistent link: https://www.econbiz.de/10011875272

Modeling heterogeneous farm responses to European Union biofuel support with a random parameter multicrop model

Koutchade, Obafèmi-Philippe; Carpentier, Alain; … - In: American journal of agricultural economics 100 (2018) 2, pp. 434-455

Persistent link: https://www.econbiz.de/10011959396

Clustering in linear and additive mixed models

2013 - 1. Aufl.

Persistent link: https://www.econbiz.de/10009749492

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