This thesis is a comprehensive comparative study of survival analysis methods, in particular the application of the Cox Proportional Hazards (CPH) model to real life data: A data set with 48 right-censored (end of study) patients suffering from multiple myeloma, and the COpenhagen Stroke study (COST) database with 993 right-censored (10 year follow-up) stroke patients. The most frequently appli...

Bayesian model averaging (BMA) is a common approach to average over alternative models; yet, it usually gets excessively concentrated around the single most probable model, therefore achieving only sub-optimal classification performance. The compression-based approach (Boullé, 2007) overcomes this problem; it averages over the different models by applying a logarithmic smoothing over the models...

This thesis consists of four papers studying structure learning and Bayesian inference in probabilistic graphical models for both undirected and directed acyclic graphs (DAGs). Paper A presents a novel algorithm, called the Christmas tree algorithm (CTA), that incrementally construct junction trees for decomposable graphs by adding one node at a time to the underlying graph. We prove that CTA w...

Ensemble classifiers combine the classification results of several classifiers. Simple ensemble methods such as uniform averaging over a set of models usually provide an improvement over selecting the single best model. Usually probabilistic classifiers restrict the set of possible models that can be learnt in order to lower computational complexity costs. In these restricted spaces, where inco...

In order to defend against extraordinary intelligent attacks in the era of rapidly growing information and technology nowadays, effective and efficient intrusion detection models are needed to detect and prevent intrusion promptly. Bayesian network (BN) classifiers with powerful reasoning capabilities have been increasingly utilized to detect intrusion attacks with reasonable accuracy and effic...

Projections of future climatic changes are a key input to the design of climate change mitigation and adaptation strategies. Current climate change projections are deeply uncertain. This uncertainty stems from several factors, including parametric and structural uncertainties. One common approach to characterize and, if possible, reduce these uncertainties is to confront (calibrate in a broad s...

Macroeconomic and financial indicators have a significant impact on the exchange market pressure (EMP) in Turkey. Despite huge amount of literature subject, there is no study focusing Turkey that takes into account role model uncertainty pressure. The should be taken consideration, given lack unique theoretical framework markets set numerous explanatory variables. Bayesian averaging (BMA) techn...

We use Bayesian Model Averaging (BMA) to forecast real-time measures of economic activity using a large set of possible predictors. The set of potential predictors includes option-adjusted credit spreads—in addition to a large number of other asset market indicators—based on bond portfolios sorted by maturity and credit risk as measured by the issuer’s distance-to-default. The portfolios are co...

The Hong Kong-Zhuhai-Macao Bridge (HZMB) is an important transportation facility connecting Kong, Zhuhai, and Macao. Thus, analyzing the characteristics of cross-border behavior becomes crucial for enhancing smart travel experience HZMB. Discrete choice models (e.g., logit models) are commonly used to describe mode behavior. Multinomial (MNL) subjected independence irrelevant alternatives (IIA)...