Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"Pseudo-likelihood"”.
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Pseudo-likelihood estimation of multidimensional polytomous item response theory models
This Dissertation was approved for publication on 2016-06-24 at 13:03.
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Modelling probabilities of corporate default
… using classical statistical frequentist likelihood estimation and one-world-view pseudo-likelihood estimation. We improve the initial estimates from our pseudo-likelihood estimation by using Sequential Monte Carlo techniques and pseudo-Bayesian inference. With these techniques, we …
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Analyzing Incomplete Longitudinal Binary Data Using Approximate Likelihood Methods
… the missing data model into the observed data likelihood function. We investigate two approximate likelihood methods, bivariate pseudo-likelihood (BPL) of Sinha et al. (2011) and independent pseudo-likelihood (IPL) of Troxel et al. (1998), along with the exact likelihood, for analyzing …
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Mdl-Based Band Selection and Adaptive Penalties for Hyperspectral Image Segmentation
… chooses the penalty parameters to maximize the pseudo-likelihood (PL) of the current image was developed by Lakshmanan and Derin, but it uses a costly simulated-annealing algorithm. We use a decoupling argument to find simple, closed-form solutions for the PL penalty parameters of a globally …
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A Dynamic Model of Land Use Change With Spatially Explicit Data
… of the parameters of interest we use a pseudo-maximum likelihood estimator, the Nested Pseudo-Likelihood algorithm. We tested our model using satellite images and other ancillary data for an area in Panama. We calibrated the model using three time periods (1985, 1987, and 1997) and the …
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Loglinear Models as Item Response Models
… has been the high computational cost of maximum likelihood estimation (MLE), due to the fact that the number of response patterns grows exponentially as the number of items increases. To solve this computational problem, a pseudo-likelihood estimation (PLE) method is proposed and it dramatically …
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Semi-supervised and active training of conditional random fields for activity recognition
… conditional entropy with labeled conditional pseudo-likelihood. The sVEB algorithm reduces the overall system cost as well as the human labeling cost required during training, which are both important considerations in building real world inference systems. Moreover, we propose an active …
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Modeling longitudinal data with interval censored anchoring events
… of the error term. The second model was likelihood based, which extended the classic mixed-effects models to the situation that the origin of the time scale for analysis was interval censored. For the purpose of large-sample statistical inference in both models, we studied the asymptotic …
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Estimation and forecasting team strength dynamics in football : investigation into structural breaks
… matches. This weighting scheme means that a pseudo-likelihood is used to estimate strength parameters. A rolling window approach is used to obtain a time series for the attack and defence strengths of teams in order to investigate the presence of structural breaks. We show that structural …
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Dynamic Discrete Choice Estimation using Reinforcement Learning with Applications in Online Food Markets
… Conditional Choice Simulation (CCS), and Nested Pseudo-Likelihood (NPL). The chapter discusses how incorporating both tabular RL methods and those using function or policy approximation into the DDC estimation process can reduce computation time and improve scalability in high-dimensional …