Global ETD Search
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Showing 1 to 12 of 12 for “"Semiparametric regression"”.
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On semiparametric regression and data mining
Semiparametric regression is playing an increasingly large role in the analysis of datasets exhibiting various complications (Ruppert, Wand & Carroll, 2003). In particular semiparametric regression a plays prominent role in the area of data mining where such complications are numerous (Hastie, …
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Semiparametric Regression Methods with Covariate Measurement Error
… with error. When mismeasured data is used in a regression analysis, not accounting for the measurement error can lead to incorrect inference about the relationships between the covariates and the response. We investigate measurement error in the covariates of two types of regression models. For …
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Semiparametric Regression Under Left-Truncated and Interval-Censored Competing Risks Data and Missing Cause of Failure
… exible tool, the R package intccr, that performs semiparametric regression analysis on the CIF for interval-censored competing risks data. Second, we adopt the augmented inverse probability weighting method to deal with both interval censoring and missing event types. We show that the resulting …
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Semiparametric Techniques for Response Surface Methodology
… settings which are common in RSM. Therefore, semiparametric regression techniques are proposed for use in the RSM setting. These methods will be applied to an elementary RSM problem as well as the robust parameter design problem.
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Two Essays on Equity Mutual Funds
… strategically altering portfolio risk. Using the semiparametric regression model proposed by Chevalier and Ellison (1997), we show that the flow-performance relationship has become linear in recent years (2000-2009) and fund managers no longer respond to such incentives. Fund managers, however, …
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Bayesian Multilevel-multiclass Graphical Model
… Another one is to select Gaussian process in semiparametric multi-kernel machine regression. The first problem is approached by Gaussian graphical model. In this project, I consider learning multiple connected graphs among multilevel variables from unknown classes. I esti- mate the classes of …
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Estimation and Testing Methods for Monotone Transformation Models
… models that contains many important semiparametric regression models as special cases. It develops a self-induced smoothing method for estimating the regression coefficients of these models, resulting in simultaneous point and variance estimations. The self-induced smoothing does not …
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Risk of Lower Extremity Amputation Revision in Patients with Peripheral Vascular Disease Adjusting for a Competing Risk of Death
… reamputation were developed using multivariable regression on the interval-censored competing risks data using semiparametric regression on the cumulative incidence function. Results: The cumulative incidences of LEA revision and revision-free mortality within one year of index amputation are …
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Semiparametric Bayesian Approach using Weighted Dirichlet Process Mixture For Finance Statistical Models
… under three research topics. The first one is semiparametric cubic spline regression where we adopt a nonparametric prior for error terms in order to automatically handle heterogeneity of measurement errors or unknown mixture distribution, the second one is to provide an innovative way to …
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Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data
Semiparametric modeling is a hybrid of the parametric and nonparametric modelings where some function forms are known and others are unknown. In this dissertation, we have made several contributions to semiparametric modeling based on the single index model related to the following three topics: …
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Semiparametric and Nonparametric Methods for Complex Data
… We have then provided several contributions to semiparametric and nonparametric methods for dealing with the following problems: the first is to propose a method for testing the significance of a functional association under the matched study; the second is to develop a method to simultaneously …