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Showing 1 to 6 of 6 for “"Expectation-maximization algorithms"”.
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Accurate Estimation of Isoform and Gene Expression Levels from Next Generation Sequencing Data
… <p>In this thesis we present two novel expectation-maximization algorithms for inference of isoform- and/or gene-specific expression levels from RNA-Seq and DGE data and a comparison of estimation performance of the two transcriptome sequencing protocols.</p> <p>The first algorithm, …
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Dichotomous and polytomous item response model estimation using the marginal maximum likelihood and the EM algorithm
… was applied to this dataset using GLIM. The Expectation-Maximization algorithm is an iterative algorithm for Marginal Likelihood Estimation in the presence of unobserved random variables, in this case represented by the respondents' latent traits.
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Latent class profile analysis : inference, estimation and its applications
… a latent class-profile analysis, we test both algorithms on synthesized data sets to evaluate their performances in model selection problems.Once a model is selected, the model parameters are needed to be estimated. The expectation-maximization algorithm (Dempster et al., 1977) and the data …
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Exact property estimation from diffusion Monte Carlo with minimal stochastic reconfiguration /
… Carlo (DMC) algorithm to estimate the exact expectation values, ($o|^|^o), of multiplicative operators, such as polarizabilities and high-order hyperpolarizabilities, for isolated atoms and molecules. The existing forward-walking pure diffusion Monte Carlo (FW-PDMC) algorithm which attempts …
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Information Processing for Biological Signals: Application to Laser Doppler Vibrometry
… on a graph. When the graph is a tree, efficient algorithms exist to compute sum-marginals or max-marginals of the joint distribution. Some of the variables correspond to the measured signal, while others may represent the hidden internal dynamics that generate the observed data. Three levels of …