1 |
Fitting factor models for ranking data using efficient EM-type algorithmsLee, Chun-fan., 李俊帆. January 2002 (has links)
published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy
|
2 |
Statistical models for catch-at-length data with birth cohort information /Chung, Sai-ho. January 2005 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2006.
|
3 |
Inferential methods for censored bivariate normal dataKim, Jeong-Ae. Balakrishnan, N., January 1900 (has links)
Thesis (Ph.D.)--McMaster University, 2004. / Supervisor: N. Balakrishnan. Includes bibliographical references (p. 186-191).
|
4 |
Improved iterative schemes for REML estimation of variance parameters in linear mixed modelsKnight, Emma Jane. January 2008 (has links)
Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, Discipline of Biometrics SA, 2008. / "October 2008" Includes bibliography (p. 283-290) Also available in print form.
|
5 |
Statistical models for catch-at-length data with birth cohort informationChung, Sai-ho. January 2005 (has links)
Thesis (Ph. D.)--University of Hong Kong, 2006. / Also available in print.
|
6 |
Sequence comparison and stochastic model based on multiorder Markov modelsFang, Xiang. January 2009 (has links)
Thesis (Ph.D.)--University of Nebraska-Lincoln, 2009. / Title from title screen (site viewed February 25, 2010). PDF text: ii, 93 p. : ill. ; 1 Mb. UMI publication number: AAT 3386580. Includes bibliographical references. Also available in microfilm and microfiche formats.
|
7 |
Distributed estimation in resource-constrained wireless sensor networksLi, Junlin. January 2008 (has links)
Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Ghassan AlRegib; Committee Member: Elliot Moore; Committee Member: Monson H. Hayes; Committee Member: Paul A. Work; Committee Member: Ying Zhang. Part of the SMARTech Electronic Thesis and Dissertation Collection.
|
8 |
Calibration of multivariate generalized hyperbolic distributions using the EM algorithm, with applications in risk management, portfolio optimization and portfolio credit riskHu, Wenbo. Kercheval, Alec. January 2005 (has links)
Thesis (Ph. D.)--Florida State University, 2005. / Advisor: Alec Kercheval, Florida State University, College of Arts and Sciences, Dept. of Mathemematics. Title and description from dissertation home page (viewed Jan. 26, 2006). Document formatted into pages; contains xii, 103 pages. Includes bibliographical references.
|
9 |
Estimation of individual treatment effect via Gaussian mixture modelWang, Juan 21 August 2020 (has links)
In this thesis, we investigate the estimation problem of treatment effect from Bayesian perspective through which one can first obtain the posterior distribution of unobserved potential outcome from observed data, and then obtain the posterior distribution of treatment effect. We mainly consider how to represent a joint distribution of two potential outcomes - one from treated group and another from control group, which can give us an indirect impression of correlation, since the estimation of treatment effect depends on correlation between two potential outcomes. The first part of this thesis illustrates the effectiveness of adapting Gaussian mixture models in solving the treatment effect problem. We apply the mixture models - Gaussian Mixture Regression (GMR) and Gaussian Mixture Linear Regression (GMLR)- as a potentially simple and powerful tool to investigate the joint distribution of two potential outcomes. For GMR, we consider a joint distribution of the covariate and two potential outcomes. For GMLR, we consider a joint distribution of two potential outcomes, which linearly depend on covariate. Through developing an EM algorithm for GMLR, we find that GMR and GMLR are effective in estimating means and variances, but they are not effective in capturing correlation between two potential outcomes. In the second part of this thesis, GMLR is modified to capture unobserved covariance structure (correlation between outcomes) that can be explained by latent variables introduced through making an important model assumption. We propose a much more efficient Pre-Post EM Algorithm to implement our proposed GMLR model with unobserved covariance structure in practice. Simulation studies show that Pre-Post EM Algorithm performs well not only in estimating means and variances, but also in estimating covariance.
|
10 |
Statistical models for catch-at-length data with birth cohort informationChung, Sai-ho., 鍾世豪. January 2005 (has links)
published_or_final_version / abstract / Social Sciences / Doctoral / Doctor of Philosophy
|
Page generated in 0.1095 seconds