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Full-Text Articles in Statistical Models
Bayesian Model For Detection Of Outliers In Linear Regression With Application To Longitudinal Data, Zahraa Al-Sharea
Bayesian Model For Detection Of Outliers In Linear Regression With Application To Longitudinal Data, Zahraa Al-Sharea
Graduate Theses and Dissertations
Outlier detection is one of the most important challenges with many present-day applications. Outliers can occur due to uncertainty in data generating mechanisms or due to an error in data recording/processing. Outliers can drastically change the study's results and make predictions less reliable. Detecting outliers in longitudinal studies is quite challenging because this kind of study is working with observations that change over time. Therefore, the same subject can produce an outlier at one point in time produce regular observations at all other time points. A Bayesian hierarchical modeling assigns parameters that can quantify whether each observation is an outlier …
A Bayesian Variable Selection Method With Applications To Spatial Data, Xiahan Tang
A Bayesian Variable Selection Method With Applications To Spatial Data, Xiahan Tang
Graduate Theses and Dissertations
This thesis first describes the general idea behind Bayes Inference, various sampling methods based on Bayes theorem and many examples. Then a Bayes approach to model selection, called Stochastic Search Variable Selection (SSVS) is discussed. It was originally proposed by George and McCulloch (1993). In a normal regression model where the number of covariates is large, only a small subset tend to be significant most of the times. This Bayes procedure specifies a mixture prior for each of the unknown regression coefficient, the mixture prior was originally proposed by Geweke (1996). This mixture prior will be updated as data becomes …