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Showing 1 to 8 of 8 for “"Nonparametric modeling"”.
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Nonparametric modeling of dependencies for spatial interpolation
… covariogram. Estimating this function in a nonparametric way is the theme of this thesis. If the function can be found accurately, then kriging is the optimal linear interpolation technique. A nev,· technique for variogram model selection using the derivative of the empirical variogram and …
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Bayesian Nonparametric Modeling and Theory for Complex Data
… methodological problems associated with Bayesian modeling of infinite dimensional `objects', popularly called nonparametric Bayes. The term `infinite dimensional object' can refer to a density, a conditional density, a regression surface or even a manifold. Although Bayesian density estimation as …
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Semiparametric Inference
Semi-parametric and nonparametric modeling and inference have been widely studied during the last two decades. In this manuscript, we do statistical inference based on semi-parametric and nonparametric models in several different scenarios. Firstly, we develop a semi-parametric additivity test for …
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Bayes meets Bach: applications of Bayesian statistics to audio restoration
… of an efficient initialization procedure, and a nonparametric modeling via Gaussian process is also presented.
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Semi-parametric models for response times and response accuracy in computerized testing
… responses. This broadens the scope of potential modeling approaches because response times can be analyzed in addition to analyzing the responses themselves. Current models for response times,however, mainly focus on parametric models that have the advantage of conciseness, but may suffer from a …
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Improving Electromagnetic Bias Estimates
… predicted and ground truth bias values.</p> <p>Nonparametric models have been proposed as a method to reduce the variability of EM bias estimates. Using tower data, nonparametric models developed from wind speed and significant wave height measurements are shown to provide some improvement over …
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Hurdles and solutions for cognitive diagnosis
Cognitive diagnostic modeling has become an important field of psychometric research. The models are special because they provide examinees with diagnostic information regarding whether or not they have mastered individual skills in certain area. They provide as meaningful sources of information …
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Toward Nonparametric Propensity Score Estimation With Guaranteed Covariate Balance
… performance compared to methods without modeling propensity score. </em><em>In Aim 2, we developed a propensity score analysis framework, the propensity score </em><em>with local balance (PSLB), which incorporates nonparametric propensity score models </em><em>and improves the balancing …