Browsing Statistics Doctoral Work by Title
Now showing items 1-20 of 35
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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 ... -
Bayesian Lasso Models – With Application to Sports Data
(North Dakota State University, 2018)Several statistical models were proposed by researchers to fulfill the objective of correctly predicting the winners of sports game, for example, the generalized linear model (Magel & Unruh, 2013) and the probability ... -
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, ... -
Community detection in censored hypergraph
(North Dakota State University, 2024)Network, or graph, represent relationships between entities in various applications, such as social networks, biological systems, and communication networks. A common feature in network data is the presence of community ... -
Comparing Prediction Accuracies of Cancer Survival Using Machine Learning Techniques and Statistical Methods in Combination with Data Reduction Methods
(North Dakota State University, 2022)This comparative study of five-year survival prediction for breast, lung, colon, and leukemia cancers using a large SEER dataset along with 10-fold cross-validation provided us with an insight into the relative prediction ... -
Comparing Prediction Methods of Wheat Grain Quality With the Area Under the Receiver Operating Characteristic Curves
(North Dakota State University, 2021)A widely used breeding method is genomic selection, which uses genome-wide marker coverage to predict genotypic values for quantitative traits. Genomic selection combines molecular and phenotypic data in a training population ... -
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 ... -
A Comparison of False Discovery Rate Method and Dunnett's Test for a Large Number of Treatments
(North Dakota State University, 2015)It has become quite common nowadays to perform multiple tests simultaneously in order to detect differences of a certain trait among groups. This often leads to an inflated probability of at least one Type I Error, a ... -
A Conditional Random Field (CRF) Based Machine Learning Framework for Product Review Mining
(North Dakota State University, 2019)The task of opinion mining from product reviews has been achieved by employing rule-based approaches or generative learning models such as hidden Markov models (HMMs). This paper introduced a discriminative model using ... -
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 ... -
Distributed Inference for Degenerate U-Statistics with Application to One and Two Sample Test
(North Dakota State University, 2020)In many hypothesis testing problems such as one-sample and two-sample test problems, the test statistics are degenerate U-statistics. One of the challenges in practice is the computation of U-statistics for a large sample ... -
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 ... -
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, ... -
Measuring Performance of United States Commercial and Domestic Banks and its Impact on 2007-2009 Financial Crisis
(North Dakota State University, 2019)In the analysis of efficiency measures, the statistical Stochastic Frontier Analysis (SFA) and linear programming Data Envelopment Analysis (DEA) estimators have been widely applied. This dissertation is centered around ... -
Model Validation and Diagnostis in Right Censored Regression
(North Dakota State University, 2013)When censored data are present in the linear regression setting, the Expectation-Maximization (EM) algorithm and the Buckley and James (BJ) method are two algorithms that can be implemented to fit the regression model. We ... -
Nonparametric Test for Nondecreasing Order Alternatives in Randomized Complete Block and Balanced Incomplete Block Mixed Design
(North Dakota State University, 2020)Nonparametric tests are used to test hypotheses when the data at hand violate one or more of the assumptions for parametric tests procedures. The test is an ordered alternative (nondecreasing) when there is prior information ... -
Nonparametric Tests for the Non-Decreasing and Alternative Hypotheses for the Incomplete Block and Completely Randomized Mixed Design
(North Dakota State University, 2014)This research study proposes a solution to deal with missing observations which is a common problem in real world datasets. A nonparametric approach is used because of its ease of use relative to the parametric approach ... -
Nonparametric Tests for the Umbrella Alternative in a Mixed Design for a Known Peak
(North Dakota State University, 2020)When an assumption from a parametric test cannot be verified, a nonparametric test provides a simple way of conducting a test on populations. The motivation behind conducting a test of the hypothesis is to examine the ... -
On Lasso Estimation of Linear Mixed Model for High Dimensional Longitudinal Data
(North Dakota State University, 2021)With the advancement of technology in data collection, repeated measurements with high dimensional covariates have become increasingly common. The classical statistics approach for modeling the data of this kind is via the ... -
Performance of Permutation Tests Using Simulated Genetic Data
(North Dakota State University, 2022)Disease statuses and biological conditions are known to be greatly impacted by differences in gene expression levels. A common challenge in RNA-seq data analysis is to identify genes whose mean expression levels change ...