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Now showing items 11-20 of 34
Conditional Random Field with Lasso and its Application to the Classification of Barley Genes Based on Expression Level Affected by Fungal Infection
(North Dakota State University, 2019)
The classification problem of gene expression level, more specifically, gene expression analysis, is a major research area in statistics. There are several classical methods to solve the classification problem. To apply ...
Proposed Nonparametric Tests for the Simple Tree Alternative in a Mixed Design
(North Dakota State University, 2014)
For the general alternative, many test statistics exist for the dependent and independent
variables. However, no documented test statistics exist for simple tree alternative for the dependent
variables, independent ...
Two Approaches to the Isotonic Change-Point Problem: Nonparametric and Minimax
(North Dakota State University, 2014)
A change in model parameters over time often characterizes major events. Situations in which this may arise include observing increasing temperatures, intense rainfall, and the valuation of a stock. The question is whether ...
Adaptive Two-Stage Optimal Design for Estimating Multiple EDps under the 4-Parameter Logistic Model
(North Dakota State University, 2018)
In dose-finding studies, c-optimal designs provide the most efficient design to study an interesting target dose. However, there is no guarantee that a c-optimal design that works best for estimating one specific target ...
Predicting the Outcomes of NCAA Women’s Sports
(North Dakota State University, 2017)
Sports competitions provide excellent opportunities for model building and using basic statistical methodology in an interesting way. More attention has been paid to and more research has been conducted pertaining to men’s ...
Identification of Differentially Expressed Genes When the Distribution of Effect Sizes is Asymmetric in Two Class Experiments
(North Dakota State University, 2017)
High-throughput RNA Sequencing (RNA-Seq) has emerged as an innovative and powerful technology for detecting differentially expressed genes (DE) across different conditions. Unlike continuous microarray data, RNA-Seq data ...
A Study of Influential Statistics Associated with Success in the National Football League
(North Dakota State University, 2015)
This dissertation considers the most important aspects of success in the National Football League (NFL). Success is defined, for this paper, as winning individual games in the short term, and making the playoffs over the ...
Comparing Several Modeling Methods on NCAA March Madness.
(North Dakota State University, 2015)
This year (2015), according to the AGA’s (American Gaming Association) research, nearly about 40 million people filled out about 70 million March Madness brackets (Moyer, 2015). Their objective is to correctly predict the ...
Integrative Data Analysis of Microarray and RNA-seq
(North Dakota State University, 2018)
Background: Microarray and RNA sequencing (RNA-seq) are two commonly used high-throughput technologies for gene expression profiling for the past decades. For global gene expression studies, both techniques are expensive, ...
Boundary Estimation
(North Dakota State University, 2015)
The existing statistical methods do not provide a satisfactory solution to determining the
spatial pattern in spatially referenced data, which is often required by research in many areas
including geology, agriculture, ...