We present a novel maximum-likelihood-based algorithm for estimating the distribution of alignment scores from the scores of unrelated sequences in a database search. Using a new method for measuring the accuracy of p-values, we show that our maximum-likelihood-based algorithm is more accurate...

This thesis studies local risk minimization, consistent interest-rate modeling, and their applications to life insurance.Part I considers local risk minimization, which is one possible approach to price and hedge claims in incomplete markets. In this first part, our two main results are...

When categorical data are misplaced into the wrong category, we say the data is affected by misclassification. This is common for data collection. It is well-known that naive estimators of category probabilities and coefficients for regression that ignore misclassification can be biased. In this...

Data Envelopment Analysis (DEA) is a multi-criteria data analysis methodology introduced by Charnes, Cooper, and Rhodes in 1978. Since that time, it has proven to be a valuable analysis tool for strategic, policy, and operational decision problems. Its primary use is to conduct performance...

The first part of my thesis is concerned with estimation for longitudinal data using generalized semi-parametric mixed models and multilevel generalized linear mixed models for a binary response. Likelihood based inferences are hindered by the lack of a closed form representation. Consequently,...

The goal of this dissertation is to provide a series of static and dynamic models of competitive multi-instrument, multi-sector, and multi-currency financial equilibrium which will yield the optimal composition of assets and liabilities in the portfolio of every sector of each country. The...

In ecological population management, years of animal counts are fit to nonlinear, dynamic models (e.g. the Ricker model) because the values of the parameters are of interest. The yearly counts are subject to measurement error, which inevitably leads to biased estimates and adversely affects...

This project applies the methods of functional data analysis (FDA) to intra-daily returns of US corporations. It focuses on an extension of the Capital Asset Pricing Model (CAPM) to such returns. The CAPM is essentially a linear regression with the slope coefficient . Returns of an asset are...

We propose a scaled linear mixed model to assess the effects of exposure and other covariates on multiple continuous outcomes. The most general form of the model allows a different exposure effect for each outcome. An important special case is a model that represents the exposure effects using a...