Search Results - subject:"EM Algorithm"

A new approach to Bayesian hypothesis testing

Li, Yong; Zeng, Tao; Yu, Jun - In: Journal of Econometrics 178 (2014) P3, pp. 602-612

In this paper a new Bayesian approach is proposed to test a point null hypothesis based on the deviance in a decision-theoretical framework. The proposed test statistic may be regarded as the Bayesian version of the likelihood ratio test and appeals in practical applications with three desirable...

Persistent link: https://www.econbiz.de/10010730124

A flexible parametric approach for estimating switching regime models and treatment effect parameters

Chen, Heng; Fan, Yanqin; Wu, Jisong - In: Journal of Econometrics 181 (2014) 2, pp. 77-91

In this paper, we propose a flexible, parametric class of switching regime models allowing for both skewed and fat-tailed outcome and selection errors. Specifically, we model the joint distribution of each outcome error and the selection error via a newly constructed class of multivariate...

Persistent link: https://www.econbiz.de/10011052296

Downturn Loss Given Default: Mixture distribution estimation

Calabrese, Raffaella - In: European Journal of Operational Research 237 (2014) 1, pp. 271-277

by the EM algorithm. Finally, we apply the proposed model to empirical data on Italian bank loans. …

Persistent link: https://www.econbiz.de/10011097696

Structural vector autoregressions with Markov switching: Combining conventional with statistical identification of shocks

Herwartz, Helmut; Lütkepohl, Helmut - In: Journal of Econometrics 183 (2014) 1, pp. 104-116

In structural vector autoregressive (SVAR) analysis a Markov regime switching (MS) property can be exploited to identify shocks if the reduced form error covariance matrix varies across regimes. Unfortunately, these shocks may not have a meaningful structural economic interpretation. It is...

Persistent link: https://www.econbiz.de/10011077586

A robust extension of the bivariate Birnbaum–Saunders distribution and associated inference

Vilca, Filidor; Balakrishnan, N.; Zeller, Camila Borelli - In: Journal of Multivariate Analysis 124 (2014) C, pp. 418-435

marginals are of univariate Birnbaum–Saunders type. We then develop the EM-algorithm for the maximum likelihood (ML) estimation …

Persistent link: https://www.econbiz.de/10011041898

Multivariate measurement error models using finite mixtures of skew-Student t distributions

Cabral, Celso Rômulo Barbosa; Lachos, Víctor Hugo; … - In: Journal of Multivariate Analysis 124 (2014) C, pp. 179-198

In regression models, the classical assumption of normal distribution of the random observational errors is often violated, masking some important features of the variability present in the data. Some practical actions to solve the problem, like transformation of variables to achieve normality,...

Persistent link: https://www.econbiz.de/10011041905

On bivariate Weibull-Geometric distribution

Kundu, Debasis; Gupta, Arjun K. - In: Journal of Multivariate Analysis 123 (2014) C, pp. 19-29

algorithm, and it is observed that the implementation of the EM algorithm is quite straightforward. Two data sets have been … analyzed for illustrative purposes, and it is observed that the new model and the proposed EM algorithm work quite well in … distribution has five parameters, and the maximum likelihood estimators cannot be obtained in closed form. We propose to use the EM …

Persistent link: https://www.econbiz.de/10011041954

MultiLCIRT: An R package for multidimensional latent class item response models

Bartolucci, Francesco; Bacci, Silvia; Gnaldi, Michela - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 971-985

A class of Item Response Theory (IRT) models for binary and ordinal polytomous items is illustrated and an R package for dealing with these models, named MultiLCIRT, is described. The models at issue extend traditional IRT models allowing for multidimensionality and discreteness of latent...

Persistent link: https://www.econbiz.de/10010871332

Parameter estimation via stochastic variants of the ECM algorithm with applications to plant growth modeling

Trevezas, S.; Malefaki, S.; Cournède, P.-H. - In: Computational Statistics & Data Analysis 78 (2014) C, pp. 82-99

Mathematical modeling of plant growth has gained increasing interest in recent years due to its potential applications. A general family of models, known as functional–structural plant models (FSPMs) and formalized as dynamic systems, serves as the basis for the current study. Modeling,...

Persistent link: https://www.econbiz.de/10010871385

Robust mixture regression model fitting by Laplace distribution

Song, Weixing; Yao, Weixin; Xing, Yanru - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 128-137

latent distribution, this procedure is implemented by an EM algorithm which incorporates two types of missing information …

Persistent link: https://www.econbiz.de/10010871393