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 6 of 6 for “"Semiparametric Approach"”.
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A marketing mix model developed from single source data : a semiparametric approach
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 1991.
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Statistical Analysis of Response Distribution for Dependent Data via Joint Quantile Regression
… quantile levels. Unfortunately, existing approaches find it extremely difficult to adjust for any dependency between observation units, largely because such methods are not based upon a fully generative model of the data. In this dissertation, we address this difficulty for analyzing …
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Spatial modeling, covariate measurement error and design issues in environmental epidemiology
… rates. We also extend the indiCAR method to a semiparametric mixed model framework that allows adjustment for smooth covariate effects (smooth-indiCAR). We illustrate the applicability of both methods in a distributed computing framework that enhances its application in the Big Data domain with …
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Methods for two-sample comparisons from censored time-to-event data
… two-stage bootstrap is exploited to obtain semiparametric SCBs for the difference. The two-stage bootstrap combines the classical bootstrap with a model-based regeneration of censoring indicators. Simulation studies are presented to show that the new SCBs are superior to a currently existing …
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Statistical Methods for Genetic Pathway-Based Data Analysis
… structures. For the first problem, we develop a semiparametric model via a Bayesian hierarchical framework. We model the pathway effect nonparametrically into a zero inflated Poisson hierarchical regression model with unknown link function. The nonparametric pathway effect is estimated via the …
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Cost Modeling Based on Support Vector Regression for Complex Products During the Early Design Phases
… (CA) method and Tabu-Stepwise selection approach. The CA method increases understanding and explanation of the cost analysis and helps avoid missing some cost drivers. The Tabu-Stepwise selection approach is used to select significant cost drivers and eliminate irrelevant cost drivers …