The purpose of this dissertation is to develop new statistical tools for mining big data in plant sciences. In particular, the dissertation consists of four inter-related projects to address various methodological and computational challenges in phylogenetic methods. Project 1 aims to systematically test different optimization tools and provide useful strategies to improve optimization in practice. Project 2 develops a new R package rPlant, which provides a friendly and convenient toolbox for users of iPlant. Project 3 presents a fast and effective group-screening method to identify important genetic factors in GWAS, with theoretical justifications and nice asymptotic properties. Project 4 develops a new statistical tool to identify gene-gene interactions, with the ability of handling the interactions between groups of covariates.

<p>  </p> <p>Widely recognized as bridging graduate coursework and independent research, doctoral examinations also (re)-produce disciplinary norms and map trajectories for graduate student professionalization. This institutional ethnography investigates doctoral exam processes as a component of curricular infrastructure, a term that I describe in functional, relational, temporal, and heuristic terms. This study begins with a discipline-wide survey (Chapter 3) reaching 81 PhD programs in Rhetoric and Composition, building on previous programmatic research in the field to identify constellations of exam formats and their stated purposes. From this broad view, institutional ethnography re-orients analysis by focusing on the standpoints of individual stakeholders (graduate students and faculty) and the ways that work processes point toward broader structural tendencies and assumptions.  From the survey, individual perspectives through interviews with faculty at nine different universities (Chapter 4) and a large focus group with graduate students (Chapter 5) to identify work practices and the institutional and disciplinary factors that direct them. This project yields an empirically grounded description of current graduate pedagogical practices, and through those practices, describes several contours of curricular infrastructure. Temporal boundary objects describe how the meaning and significance of an experience like a doctoral exam can change across time, yielding insight into how curricular practices transfer from one intuition to another. Institutional inertia appears as common iteration of curricular infrastructure, representing the tendency of intuitions to self-replicate and resist change, and nonverbal visually embodied actions serve as a key to understanding communication about institutions that avoids talking about institutions. The project culminates in Chapter 6 with a three-part heuristic, described as an aspect of curricular infrastructure, designed as a resource to faculty and administrators who are in decision-making positions with respect to doctoral exams.  </p>

本篇論文主要考慮成群資料的存活分析，其特點為群內個體間具有相關性，並假定群內個體具有相同但無法觀測到的事故傾向。首先，探討事故傾向服從任一連續分配時混合Weibull迴歸模式的特性，接著，推導出事故傾向服從血Inverse Gaussian吧時之混合Weibull模式，並介紹參數的估計問題。然後，推導出群內個體是否獨立之分數檢定統計量，以分別就兩種最常見的存活資料型態一完整型態與右設限型態：檢定模式中事故傾向的效應是否存在。最後，並以實例說明分數檢定之程序。 / In this paper, we study survival analysis for grouped data, where the within group correlations are considered. It is also assumed that individuals within the same group share a common but unobservable random frailty. First, we discuss the properties of the Weibull regression model mixed by any continuous distribution. Next, we derive an Inverse Gaussan mixture of Weibull regression model, and discuss the estimation problem. Then, we derive the score test for testing independence between components within the same group, where the two most common cases are discussed the complete data case and the right censoring case. Finally, the testing procedures are illustrated by two examples.