Search Results - subject:"EM ALGORITHM"

Structural Inference in Transition Measurement Error Models for Longitudinal Data

Pan, Wenqin; Lin, Xihong; Zeng, Donglin - 2006

likelihood estimation method. In view of the multidimensional integration required by full maximum likelihood estimation, an EM … algorithm is developed to calculate maximum likelihood estimators, in which Monte Carlo simulations are used to evaluate the …

Persistent link: https://www.econbiz.de/10009477335

Multivariate mixed normal conditional heteroskedasticity

Luc, BAUWENS; C.M., HAFNER; J.V.K., ROMBOUTS - Institut de Recherche Économique et Sociale (IRES), … - 2006

a maximum likelihood with the EM algorithm and Bayesian estimation with a Gibbs sampler. Finally, we apply the model to …

Persistent link: https://www.econbiz.de/10004984765

Real-time forecasting of GDP based on a large factor model with monthly and quarterly data

Schumacher, Christian; Breitung, Jörg - Deutsche Bundesbank - 2006

sample, the factors are estimated by applying an EM algorithm combined with a principal components estimator. We discuss the …

Persistent link: https://www.econbiz.de/10005083178

Multivariate mixed normal conditional heteroskedasticity

BAUWENS, Luc; HAFNER, Christian; ROMBOUTS, Jeroen - Center for Operations Research and Econometrics (CORE), … - 2006

maximum likelihood with the EM algorithm and Bayesian estimation with a Gibbs sampler. Finally, we apply the model to daily U …

Persistent link: https://www.econbiz.de/10005065329

A New Direction of Fund Rating Based on the Finite Normal Mixture Model

Gao, Zhangpeng; Rahman, Shahidur - Division of Economics, Nanyang Technological University - 2006

we estimate the model with EM algorithm by treating the group information of funds as missing information. …

Persistent link: https://www.econbiz.de/10005744859

The Stacked Leading Indicators Dynamic Factor Model: A Sensitivity Analysis of Forecast Accuracy using Bootstrapping

Grenouilleau, Daniel - Directorate-General Economic and Financial Affairs, … - 2006

computed with the EM algorithm implemented with the first few eigenvectors ordered by descending eigenvalues. A cross …

Persistent link: https://www.econbiz.de/10008595797

Modelling Dyadic Interaction with Hawkes Processes

Halpin, Peter; Boeck, Paul - In: Psychometrika 78 (2013) 4, pp. 793-814

historical dependency, while the latter is conducive to maximum likelihood estimation using the EM algorithm. We first outline …

Persistent link: https://www.econbiz.de/10010728124

An Application of EM Test for the Bayesian Change Point Problem

Variyath A. M.; Vasudevan C. V. - In: Economic Quality Control 28 (2013) 1, pp. 57-69

follow an exponential family distribution. In this approach, the expectation – maximization (EM) algorithm was used for … estimating the process parameters. In general, the EM algorithm is computationally intensive and the optimality depends on the …

Persistent link: https://www.econbiz.de/10010736171

Modeling Differential Item Functioning Using a Generalization of the Multiple-Group Bifactor Model

Jeon, Minjeong; Rijmen, Frank; Rabe-Hesketh, Sophia - In: Journal of Educational and Behavioral Statistics 38 (2013) 1, pp. 32-60

The authors present a generalization of the multiple-group bifactor model that extends the classical bifactor model for categorical outcomes by relaxing the typical assumption of independence of the specific dimensions. In addition to the means and variances of all dimensions, the correlations...

Persistent link: https://www.econbiz.de/10010739197

Estimation of the preference heterogeneity within stated choice data using semiparametric varying-coefficient methods

Hoshino, Tadao - In: Empirical Economics 45 (2013) 3, pp. 1129-1148

This study proposes the use of semiparametric varying-coefficient methods to estimate the preference heterogeneity within stated choice data. Semiparametric varying-coefficient methods have the potential to overcome the disadvantages of conventional random parameter models and latent class...

Persistent link: https://www.econbiz.de/10010794006