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Full-Text Articles in Physical Sciences and Mathematics
A Comparison Of Confidence Intervals In State Space Models, Jinyu Du
A Comparison Of Confidence Intervals In State Space Models, Jinyu Du
Statistical Science Theses and Dissertations
This thesis develops general procedures for constructing confidence intervals (CIs) of the error disturbance parameters (standard deviations) and transformations of the error disturbance parameters in time-invariant state space models (ssm). With only a set of observations, estimating individual error disturbance parameters accurately in the presence of other unknown parameters in ssm is a very challenging problem. We attempted to construct four different types of confidence intervals, Wald, likelihood ratio, score, and higher-order asymptotic intervals for both the simple local level model and the general time-invariant state space models (ssm). We show that for a simple local level model, both the …
High-Dimensional Variable Selection Via Knockoffs Using Gradient Boosting, Amr Essam Mohamed
High-Dimensional Variable Selection Via Knockoffs Using Gradient Boosting, Amr Essam Mohamed
Dissertations
As data continue to grow rapidly in size and complexity, efficient and effective statistical methods are needed to detect the important variables/features. Variable selection is one of the most crucial problems in statistical applications. This problem arises when one wants to model the relationship between the response and the predictors. The goal is to reduce the number of variables to a minimal set of explanatory variables that are truly associated with the response of interest to improve the model accuracy. Effectively choosing the true influential variables and controlling the False Discovery Rate (FDR) without sacrificing power has been a challenge …