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Articles 1 - 4 of 4
Full-Text Articles in Statistical Models
Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir
Garch Modeling Of Value At Risk And Expected Shortfall Using Bayesian Model Averaging, Ismail Kheir
Theses and Dissertations
This thesis conducts Value at Risk (VaR) and Expected Shortfall (ES) estimation using GARCH modeling and Bayesian Model Averaging (BMA). BMA considers multiple models weighted by some information criterion. Through BMA, this thesis finds that VaR and ES estimates can be improved through enhanced modeling of the data generation process.
Allocative Poisson Factorization For Computational Social Science, Aaron Schein
Allocative Poisson Factorization For Computational Social Science, Aaron Schein
Doctoral Dissertations
Social science data often comes in the form of high-dimensional discrete data such as categorical survey responses, social interaction records, or text. These data sets exhibit high degrees of sparsity, missingness, overdispersion, and burstiness, all of which present challenges to traditional statistical modeling techniques. The framework of Poisson factorization (PF) has emerged in recent years as a natural way to model high-dimensional discrete data sets. This framework assumes that each observed count in a data set is a Poisson random variable $y ~ Pois(\mu)$ whose rate parameter $\mu$ is a function of shared model parameters. This thesis examines a specific …
Analyzing Two-Year College Student Success Using Structural Equation Modeling, Jessica Taylor
Analyzing Two-Year College Student Success Using Structural Equation Modeling, Jessica Taylor
Graduate Theses, Dissertations, and Capstones
The goal of this study is to more fully understand the scope of community college student success using the principles of mindset, engagement, and college readiness. Using structural equation modeling ensures this study is able to measure the combined effects these concepts have on student success, group differences, and the combined model of student success. Findings suggest student success can be significantly impacted by self-belief and mindset behaviors that can outweigh the initial effect of academically under-prepared students. Groups included in this study are non-traditional students, minority populations, first generation students, and Pell eligible students.
On Cluster Robust Models, José Bayoán Santiago Calderón
On Cluster Robust Models, José Bayoán Santiago Calderón
CGU Theses & Dissertations
Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches …