Agent-based models (ABM) are widely used in network data analysis, and due to their simple structures and sophisticated outcomes, they serve as good tools in understanding the dynamics in networks. In this thesis, we develop an agent-based dynamic network model, and show that it can replicate the expected degree distribution...
In many scientific settings, investigators are interested in the effect of a new treatment. To have a point of comparison data is collected from patients before treatment groups are assigned. When seeking to test the presence of a significant treatment effect it may be unclear how baseline measurements should be...
Humans are remarkably efficient in learning by interacting with other people and observing their behavior. Children learn by watching their parents’ actions and mimic their behavior. When they are not sure about their parents demonstration, they communicate with them, ask questions, and learn from their feedback. On the other hand,...
Community driven development (CDD) is one of the recent approaches in the development arena that integrates people into mainstream development. Bringing people together into the development prospects through social capital is an important aspect of this approach that harnesses greater social inclusion and wider participation at the grass root level....
Scholars posit that the successful consolidation of post-communist Central and Eastern European democracies can be linked to their subsequent accession to the European Union (EU). This led observers to assume that the continued democratization of Hungarian society was assured due to their integration into EU institutions. However, since the 2010...
MSME development has emerged at the forefront of economic policy, with the majority of policy mechanisms aimed at creating the regulatory and institutional environments, which have historically proven to augment entrepreneurial activity. In the case of Europe a large portion of entrepreneurial policy resides within the European Community framework, however...
Due to recent advances in computer technology, the cost of collecting and storing data has dropped drastically. This makes it feasible to collect large amounts of information for each data point. This increasing trend in feature dimensionality justifies the need for research on variable selection. Random forest (RF) has demonstrated...
Diverse scientific fields collect multiple time series data to investigate the dynamical behavior of complex systems: atmospheric and climate science, geophysics, neuroscience, epidemiology, ecology, and environmental science. Identifying patterns of mutual dependence among such data generates valuable knowledge that can be applied either for inferential or forecasting purposes. Vector autoregressive...
Anomaly detection is the task of identifying observations (points) that differ from the majority of other points, which requires some measure of difference, or distance. Many anomaly detection methods rely on “implicit distance” measures: rather than directly calculating an explicitly defined distance, these approaches quantify a point’s “abnormality” by examining...
Randomized trials are the gold standard for the clinical assessment of a new treatment
compared to a placebo or standard of care. Often in clinical trials, patients are
accrued sequentially rather than all at once. Thus, the data from such a trial becomes
available sequentially to the researcher. Monitoring and...