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University of Illinois at Urbana-Champaign
Bayesian Inference in Nonparametric Logistic Regression
Abstract
dc:descriptionWe consider the problem of regressing a dichotomous response variable on a predictor variable. Our interest is in modelling the probability of occurrence of the response as a function of the predictor variable, and in inferences about the estimated function. The log-odds (logit) of the probability is estimated nonparametrically, using generalized smoothing splines.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Statistics
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2014
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Raghavan, Nandini
- Contributors dc:contributor
-
- Cox, Dennis D.
Subjects
dc:subject × 1Identifiers
dc:identifier.*- Identifier
- (UMI)AAI9411757
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/72584