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.
Results
Showing 1 to 8 of 8 for “"Dimension Reduction Methods"”.
-
Nonparametric variable selection and dimension reduction methods and their applications in pharmacogenomics
… response. Because whole-genome data are high dimensional and their relationships to drug response are complicated, we are developing a variety of nonparametric methods, including variable selection using local regression and extended dimension reduction techniques, to detect nonlinear patterns …
-
Dimension reduction methods for quantifying local variable importance and the statistical analysis of network data
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01
-
Development and application of calibration free techniques for reaction profiling
In this technological information age, dimension reduction methods are key because they enable the almost instantaneous extraction of relevant information from large complex data sets. This is particularly crucial within the process analytical environment where "right-first-time" and "just-in-time" …
-
On testing common indices for several multi-index models: A link-free approach
<p>"To avoid the curse of dimensionality, and to help us better understand the structure of the high dimensional data, methods for dimension reduction are clearly called for. The common linear dimension reduction techniques for single population include principal component analysis (PCA) which is …
-
Sufficient Dimension Reduction with Missing Data
Existing sufficient dimension reduction (SDR) methods typically consider cases with no missing data. The dissertation aims to propose methods to facilitate the SDR methods when the response can be missing. The first part of the dissertation focuses on the seminal sliced inverse regression (SIR) …
-
Identification of genomic factors using family-based association studies
… of genetic relatedness of samples. Many methods have been proposed to guard against these spurious associations. Here we focus on multi-locus association studies of quantitative traits and the case-control status, and propose algorithms that take into consideration of genetic related …
-
Gradient-based dimension reduction for Bayesian inverse problems and simulation-based inference
… demanding. This thesis focuses on Bayesian methods for inverse problems governed by partial differential equations and for simulation-based (likelihood-free) inference: in both settings, the high dimensionality of model parameters and/or data can render naïve posterior exploration …