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On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar
On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar
FIU Electronic Theses and Dissertations
Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produces a higher MSE than the ridge regression estimator. A Monte Carlo …
Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov
Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov
Publications and Research
We develop a simulation model for predicting the outcome of the US Presidential election based on simulating the distribution of the Electoral College. The simulation model has two parts: (a) estimating the probabilities for a given candidate to win each state and DC, based on state polls, and (b) estimating the probability that a given candidate will win at least 270 electoral votes, and thus win the White House. All simulations are coded using the high-level, open-source programming language R. One of the goals of this paper is to promote computational thinking in any STEM field by illustrating how probabilistic …