Index Catalog // ScholarsArchive@OSU

Bayesian inference for the Weibull distribution

Creator:: Bogdanoff, David Allen
Abstract:: Bayesian inferential methods for the two parameter Weibull (and extreme-value distribution) are presented in a life-testing context. A practical method of calculating posterior distributions of the two parameters and a large class of functions of the parameters is presented. The emphasis is for the situation where the sample information is...
Resource Type:: Dissertation
Full Text:: confidence limits given by the Bayesian method, as is known from the general theory of Bayesian procedures

Bayes-Fiducial inference from censored normal data

Creator:: Wille, Jerald Robert
Resource Type:: Dissertation
Full Text:: Statement of the Problem 1 Methods of Estimation 3 II. UNDERLYING THEORY AND CHOICE OF PRIOR DISTRIBUTION

Density estimation using orthogonal series : a Bayesian approach

Creator:: Pointer, Patrick C.
Resource Type:: Dissertation
Full Text:: USING ORTHOGONAL SERIES -A BAYESIAN APPROACH Redacted for Privacy Abstract approved: Dr. H. D. Brunk

Nonparametric estimation of univariate and mixing densities : a Bayesian Least Squares approach

Creator:: Shih, John I.
Resource Type:: Dissertation
Full Text:: Densities--A Bayesian Least Squares Approach AN ABSTRACT OF THE THESIS OF JOHN I SHIN for the degree of

Optimal inference with local expressions

Creator:: Borujerdi, Mohammad
Abstract:: Probabilistic inference using Bayesian networks is now a well-established approach for reasoning under uncertainty. Among many e ciency-driven tech- niques which have been developed, the Optimal Factoring Problem (OFP) is distinguished for presenting a combinatorial optimization point of view on the problem. The contribution of this thesis is to extend...
Resource Type:: Dissertation
Full Text:: Bayesian networks as a combinatorial optimization problem. Parallel to value sets algebra theory local

Analysis of Bayesian anytime inference algorithms

Creator:: Burgess, Scott Alan
Abstract:: This dissertation explores and analyzes the performance of several Bayesian anytime inference algorithms for dynamic influence diagrams. These algorithms are compared on the On-Line Maintenance Agent testbed, a software artifact permitting comparison of dynamic reasoning algorithms used by an agent on a variety of simulated maintenance and monitoring tasks. Analysis...
Resource Type:: Dissertation
Full Text:: specific probability queries in Bayesian networks, algorithms for answering decision queries in influence

Uses of Bayesian posterior modes in solving complex estimation problems in statistics

Creator:: Lin, Lie-fen
Abstract:: In Bayesian analysis, means are commonly used to summarize Bayesian posterior distributions. Problems with a large number of parameters often require numerical integrations over many dimensions to obtain means. In this dissertation, posterior modes with respect to appropriate measures are used to summarize Bayesian posterior distributions, using the Newton-Raphson method...
Resource Type:: Dissertation
Full Text:: Uses of Bayesian posterior modes in solving complex

Dependent evidence in reasoning with uncertainty

Creator:: Ling, Xiaoning
Abstract:: The problem of handling dependent evidence is an important practical issue for applications of reasoning with uncertainty in artificial intelligence. The existing solutions to the problem are not satisfactory because of their ad hoc nature, complexities, or limitations. In this dissertation, we develop a general framework that can be used...
Resource Type:: Dissertation
Full Text:: for Theory of Evidence 19 3.2.2. Statistical Dependence Parameters for Odds-likelihood-ratios 21 3.3

Multiple comparisons for the balanced two-way factorial : an applied Bayes rule (k-ratio) approach

Creator:: Pennello, Gene A.
Resource Type:: Dissertation
Full Text:: from the frequentist, decision-theoretic, Bayesian, and fiducial approaches, and is one I feel

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Creator:: Wilson, Aaron
Abstract:: How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...
Resource Type:: Dissertation
Full Text:: . Importantly, Bayesian theory provides an optimal means of updating the agent’s knowledge such that decisions

ScholarsArchive@OSU

Bayesian inference for the Weibull distribution

Bayes-Fiducial inference from censored normal data

Density estimation using orthogonal series : a Bayesian approach

Nonparametric estimation of univariate and mixing densities : a Bayesian Least Squares approach

Optimal inference with local expressions

Analysis of Bayesian anytime inference algorithms

Uses of Bayesian posterior modes in solving complex estimation problems in statistics

Dependent evidence in reasoning with uncertainty

Multiple comparisons for the balanced two-way factorial : an applied Bayes rule (k-ratio) approach

Bayesian methods for knowledge transfer and policy search in reinforcement learning

Limit your search

Academic Affiliation

Advisor

Commencement Year

Committee Member

Creator

Date

Decade

Degree Field

Degree Level

Degree Name

Language

License

Non-Academic Affiliation

Peer Reviewed

Resource Type

Rights Statement

Subject

Search Constraints

Search Results

Limit your search