Inferences for joint modelling of repeated ordinal scores and time to event data.
Chakraborty, Arindom, Das, Kalyan (2010)
Computational & Mathematical Methods in Medicine
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Chakraborty, Arindom, Das, Kalyan (2010)
Computational & Mathematical Methods in Medicine
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Vernic, Raluca, Teodorescu, Sandra, Pelican, Elena (2009)
Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică
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G. Qian, R. M. Huggins, D. Z. Loesch (2004)
Discussiones Mathematicae Probability and Statistics
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An extension of the Rasch model with correlated latent variables is proposed to model correlated binary data within families. The latent variables have the classical correlation structure of Fisher (1918) and the model parameters thus have genetic interpretations. The proposed model is fitted to data using a hybrid of the Metropolis-Hastings algorithm and the MCEM modification of the EM-algorithm and is illustrated using genotype-phenotype data on a psychological subtest in families...
Joanna Polańska (2003)
International Journal of Applied Mathematics and Computer Science
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A haplotype analysis is becoming increasingly important in studying complex genetic diseases. Various algorithms and specialized computer software have been developed to statistically estimate haplotype frequencies from marker phenotypes in unrelated individuals. However, currently there are very few empirical reports on the performance of the methods for the recovery of haplotype frequencies. One of the most widely used methods of haplotype reconstruction is the Maximum Likelihood method,...
Estelle Kuhn, Marc Lavielle (2004)
ESAIM: Probability and Statistics
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The stochastic approximation version of EM (SAEM) proposed by Delyon et al. (1999) is a powerful alternative to EM when the E-step is intractable. Convergence of SAEM toward a maximum of the observed likelihood is established when the unobserved data are simulated at each iteration under the conditional distribution. We show that this very restrictive assumption can be weakened. Indeed, the results of Benveniste et al. for stochastic approximation with markovian perturbations are used...
Sophie Donnet, Adeline Samson (2008)
ESAIM: Probability and Statistics
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Non-linear mixed models defined by stochastic differential equations (SDEs) are considered: the parameters of the diffusion process are random variables and vary among the individuals. A maximum likelihood estimation method based on the Stochastic Approximation EM algorithm, is proposed. This estimation method uses the Euler-Maruyama approximation of the diffusion, achieved using latent auxiliary data introduced to complete the diffusion process between each pair of measurement instants. A...
Sparks, Ross (2004)
Journal of Applied Mathematics and Decision Sciences
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Barbulescu, Alina, Bautu, Elena (2009)
Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică
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