Search Results - subject:"EM Algorithm"

EM algorithm for one-shot device testing under the exponential distribution

Balakrishnan, N.; Ling, M.H. - In: Computational Statistics & Data Analysis 56 (2012) 3, pp. 502-509

The EM algorithm is a powerful technique for determining the maximum likelihood estimates (MLEs) in the presence of … conditions rather than on the real lifetimes of the devices under test. Here, we develop the EM algorithm for such data under the … recently by Fan et al. (2009). Here, through a simulation study, we show that the EM algorithm and the mentioned Bayesian …

Persistent link: https://www.econbiz.de/10011056553

Analytic calculations for the EM algorithm for multivariate skew-t mixture models

Vrbik, I.; McNicholas, P.D. - In: Statistics & Probability Letters 82 (2012) 6, pp. 1169-1174

The em algorithm can be used to compute maximum likelihood estimates of model parameters for skew-t mixture models. We …

Persistent link: https://www.econbiz.de/10011039827

Multivariate random effect models with complete and incomplete data

Chipperfield, James O.; Steel, David G. - In: Journal of Multivariate Analysis 109 (2012) C, pp. 146-155

uses the EM algorithm to maximise the hierarchical likelihood (HL). The HL estimates are often the same as the REML and …

Persistent link: https://www.econbiz.de/10011041988

Discretized Time and Conditional Duration Modelling for Stock Transaction Data

Brännäs, Kurt; Simonsen, Ola - Institutionen för Nationalekonomi, Umeå Universitet - 2003

compared in a Monte Carlo experiment. An EM-algorithm accounting for the discrete data performs better than those which do not …

Persistent link: https://www.econbiz.de/10005651936

Estimation of the mean AUC of the xenoestrogens daidzein, bisphenol A, and p-tert-octylphenol

Selinski, Silvia; Degen, Gisela H. - 2003

Potentially adverse human and environmental effects due to hormone mimicry of environmental estrogens are a matter of current concern. Environmental estrogens belong to the so-called endocrine active compounds (EAC), which alter signalling processes of the endocrine system leading to a broad...

Persistent link: https://www.econbiz.de/10010475813

Estimation of the mean AUC of the xenoestrogens daidzein, bisphenol A, and p-tert-octylphenol

Selinski, Silvia; Degen, Gisela H. - 2003

Persistent link: https://www.econbiz.de/10010306261

Modelling High-Dimensional Data by Mixtures of Factor Analyzers

McLachlan, G. J.; Peel, D.; Bean, R. W. - 2003

We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is...

Persistent link: https://www.econbiz.de/10009447914

Likelihood-based estimation of latent generalised ARCH structures

Fiorentini, Gabriele; Sentana, Enrique; Shephard, Neil - London School of Economics (LSE) - 2003

chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a …

Persistent link: https://www.econbiz.de/10010884643

Estimation of the mean AUC of the xenoestrogens daidzein, bisphenol A, and p-tert-octylphenol

Selinski, Silvia; Degen, Gisela H. - Institut für Wirtschafts- und Sozialstatistik, … - 2003

Persistent link: https://www.econbiz.de/10009295167

Fund Rating Model Based on Finite Normal Mixture Distribution

Gao, Zhangpeng; Rahman, Shahidur; Rahman, Shafiqur - In: Review of Pacific Basin Financial Markets and Policies … 14 (2011) 01, pp. 1-33

performance groups in the model. We then employ expectation and maximization (EM) algorithm to estimate the model. Based on the …

Persistent link: https://www.econbiz.de/10008863009