111 |
Reliability growth models and reliability acceptance sampling plans from a Bayesian viewpoint林達明, Lin, Daming. January 1995 (has links)
published_or_final_version / Statistics / Doctoral / Doctor of Philosophy
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Bayesian analysis of errors-in-variables in generalized linear models鄧沛權, Tang, Pui-kuen. January 1992 (has links)
published_or_final_version / Statistics / Doctoral / Doctor of Philosophy
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113 |
Development of high performance implantable cardioverter defibrillatorbased statistical analysis of electrocardiographyKwan, Siu-ki., 關兆奇. January 2007 (has links)
published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
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Bayesian carrier frequency offset estimation in orthogonal frequency division multiplexing systemsCai, Kun, 蔡琨 January 2009 (has links)
published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy
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Online auction price prediction: a Bayesian updating framework based on the feedback historyYang, Boye., 扬博野. January 2009 (has links)
published_or_final_version / Business / Master / Master of Philosophy
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The effectiveness of hedge fund strategies and managers’ skills during market crises: a fuzzy, non-parametric and Bayesian analysis05 November 2012 (has links)
Ph.D. / This thesis investigates the persistence of hedge fund managers’ skills, the optimality of strategies they use to outperform consistently the market during periods of boom and/or recession, and the market risk encountered thereby. We consider a data set of monthly investment strategy indices published by Hedge Fund Research group. The data set spans from January 1995 to June 2010. We divide this sample period into four overlapping sub- sample periods that contain different economic market trends. We define a skilled manager as a manager who can outperform the market consistently during two consecutive sub-sample periods. To investigate the presence of managerial skills among hedge fund managers we first distinguish between outperformance, selectivity and market timing skills. We thereafter employ three different econometric models: frequentist, Bayesian and fuzzy regression, in order to estimate outperformance, selectivity and market timing skills using both linear and quadratic CAPM. Persistence in performance is carried out in three different fashions: contingence table, chi-square test and cross-sectional auto-regression technique. The results obtained with the first two probabilistic methods (frequentist and Bayesian) show that fund managers have skills to outperform the market during the period of positive economic growth (i.e. between sub-sample period 1 and sub-sample period 3). This market outperformance is due to both selectivity skill (during sub-sample period 2 and sub-sample period 3), and market timing skill (during sub-sample period 1 and sub- sample period 2). These results contradict the EMH and suggest that the “market is not always efficient,” it is possible to make abnormal rate of returns.However, the results obtained with the uncertainty fuzzy credibility method show that dispite the presence of few fund managers who possess selectivity skills during bull market period (sub-sample period 2 and sub-sample period 3), and market timing skills during recovery period (sub-sample period 3 and sub-sample period 4); there is no evidence of overall market outperformance during the entire sample period. Therefore the fuzzy credibility results support the appeal of the EMH according to which no economic agent can make risk-adjusted abnormal rate of return. The difference in findings obtained with the probabilistic method (frequentist and Bayesian) and uncertainty method (fuzzy credibility theory) is primarily due to the way uncertainty is modelled in the hedge fund universe in particular and in financial markets in general. Probability differs fundamentally from uncertainty: probability assumes that the total number of states of economy is known, whereas uncertainty assumes that the total number of states of economy is unknown. Furthermore, probabilistic methods rely on the assumption that asset returns are normally distributed and that transaction costs are negligible.
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Generalizing the number of states in Bayesian belief propagation, as applied to portfolio management.Kruger, Jan Walters. January 1996 (has links)
A research report submitted to the Faculty of Science, University of the
Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the
degree of Master of' Science. / This research report describes the use or the Pearl's algorithm in Bayesian belief
networks to induce a belief network from a database. With a solid grounding in
probability theory, the Pearl algorithm allows belief updating by propagating
likelihoods of leaf nodes (variables) and the prior probabilities.
The Pearl algorithm was originally developed for binary variables and a
generalization to more states is investigated.
The data 'Used to test this new method, in a Portfolio Management context, are the
Return and various attributes of companies listed on the Johannesburg Stock
Exchange ( JSE ).
The results of this model is then compared to a linear regression model. The
bayesian method is found to perform better than a linear regression approach. / Andrew Chakane 2018
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Various Approaches on Parameter Estimation in Mixture and Non-Mixture Cure ModelsUnknown Date (has links)
Analyzing life-time data with long-term survivors is an important topic in
medical application. Cure models are usually used to analyze survival data with the
proportion of cure subjects or long-term survivors. In order to include the propor-
tion of cure subjects, mixture and non-mixture cure models are considered. In this
dissertation, we utilize both maximum likelihood and Bayesian methods to estimate
model parameters. Simulation studies are carried out to verify the nite sample per-
formance of the estimation methods. Real data analyses are reported to illustrate
the goodness-of- t via Fr echet, Weibull and Exponentiated Exponential susceptible
distributions. Among the three parametric susceptible distributions, Fr echet is the
most promising.
Next, we extend the non-mixture cure model to include a change point in a covariate
for right censored data. The smoothed likelihood approach is used to address the
problem of a log-likelihood function which is not di erentiable with respect to the
change point. The simulation study is based on the non-mixture change point cure
model with an exponential distribution for the susceptible subjects. The simulation
results revealed a convincing performance of the proposed method of estimation. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection
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Bayesian approach to an exponential hazard regression model with a change pointUnknown Date (has links)
This thesis contains two parts. The first part derives the Bayesian estimator of
the parameters in a piecewise exponential Cox proportional hazard regression model,
with one unknown change point for a right censored survival data. The second part
surveys the applications of change point problems to various types of data, such as
long-term survival data, longitudinal data and time series data. Furthermore, the
proposed method is then used to analyse a real survival data. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection
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Analysis of multivariate probit model in several populations. / CUHK electronic theses & dissertations collectionJanuary 2007 (has links)
Keywords: MCEM algorithm; Gibbs sampler; Multivariate probit model; Multi-group; BIC. / The main purpose of this paper is to develop maximum likelihood and Bayesian approach for the multivariate probit model in several populations. A Monte Carlo EM algorithm is proposed for obtaining the maximum likelihood estimates and the Gibbs sampler is used to produce the joint Bayesian estimates. To test hypotheses involving constraints among the structural parameters of MP model across groups, we use the method of Bayesian Information Criterion(BIC). The simulation study will be given to certify the accuracy of our algorithm. / Yu, Yin. / "March 2007." / Adviser: Sik Yum Lee. / Source: Dissertation Abstracts International, Volume: 68-09, Section: B, page: 6054. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 135-137). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.
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