There are two topics in this dissertation. The first topic is 'Smoothing Parameter Selection in Nonparametric Generalized Linear Models via Sixth-order Laplace Approximation' and the second topic is 'Smoothing Spline-based Score Tests for Proportional Hazards Models'.We present a new approach...

To develop and validate a general method (called regression risk analysis) to estimate adjusted risk measures from logistic and other nonlinear multiple regression models. We show how to estimate standard errors for these estimates. These measures could supplant various approximations (e.g.,...

Logistic regression analysis can provide an estimate of the odds ratio (OR), adjusted for a number of confounders. It is known that it is approximately equal to the associated adjusted relative risk (RR) if the incidence of an outcome of interest is rare in a cohort study or a clinical trial...

In the dissertation, we study the statistical evaluation of treatment comparisons by evaluating the relative comparison of survival experiences between two treatment groups. We construct confidence interval and simultaneous confidence bands for the ratio and odds ratio of two survival functions...

Government

Valuing American options is a central problem in option pricing since the early-exercise feature is very common among financial or insurance derivatives products. For high-dimensional American options, Monte Carlo simulation is generally regarded as the only viable approach to price them, and...

Incluye bibliografía ; In this paper I consider a model for the heterogeneity and dynamics of the conditional mean and the conditional variance of standarized individual wages. In particular, I propose a dynamic panel data model with individual effects both in the mean and in a conditional ARCH...

En este trabajo se estudia la estimación de modelos no lineales de datos de panel que incluyen efectos fijos múltiples. La estimación de estos modelos es complicada tanto por la dificultad de estimar especificaciones con miles de coeficientes, como por el problema de los parámetros...

On-Line Analytical Processing (OLAP) aims at gaining useful information quickly from large amounts of data residing in a data warehouse. To improve the quickness of response to queries, pre-aggregation is a useful strategy. However, it is usually impossible to pre-aggregate along all...