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Full-Text Articles in Physical Sciences and Mathematics

Nonparametric Tests For Replicated Latin Squares, Joseph Yang Jun 2023

Nonparametric Tests For Replicated Latin Squares, Joseph Yang

Dissertations

Two classes of nonparametric procedures for a replicated Latin square design that test for both general and increasing alternatives are developed. The two classes of procedures are similar in the sense that both transform the data so that existing well-known tests for randomized complete block designs can be utilized. On the other hand, the two classes differ in the way that the data is transformed - one class essentially aggregates the data while the other class aligns the data. Within these contexts, the exact distributions and asymptotic distributions are discussed, when applicable. The exact distributions are easily computed using the …


Bayesian Experimental Design For Control And Surveillance In Epidemiology, Bren Case Jan 2023

Bayesian Experimental Design For Control And Surveillance In Epidemiology, Bren Case

Graduate College Dissertations and Theses

Effective public health interventions must balance an array of interconnected challenges, and decisions must be made based on scientific evidence from existing information. Building evidence requires extrapolating from limited data using models. But when data are insufficient, it is important to recognize the limitations of model predictions and diagnose how they can be improved. This dissertation shows how principles from Bayesian experimental design can be applied to surveillance and control efforts to allow researchers to get more out of their data and direct limited resources to best effect. We argue a Bayesian perspective on data gathering, where design decisions are …


Orthogonal Arrays And Legendre Pairs, Kristopher N. Kilpatrick Sep 2022

Orthogonal Arrays And Legendre Pairs, Kristopher N. Kilpatrick

Theses and Dissertations

Well-designed experiments greatly improve test and evaluation. Efficient experiments reduce the cost and time of running tests while improving the quality of the information obtained. Orthogonal Arrays (OAs) and Hadamard matrices are used as designed experiments to glean as much information as possible about a process with limited resources. However, constructing OAs and Hadamard matrices in general is a very difficult problem. Finding Legendre pairs (LPs) results in the construction of Hadamard matrices. This research studies the classification problem of OAs and the existence problem of LPs. In doing so, it makes two contributions to the discipline. First, it improves …


Experimental Design On High-Speed Sliding Wear, Irene D. Liew Mar 2022

Experimental Design On High-Speed Sliding Wear, Irene D. Liew

Theses and Dissertations

The purpose of this research is to develop, conduct, and analyze an experimental design that characterizes wear rates of various materials sliding at high speeds along AISI 4340 steel. This work is in support of Holloman Air Force Base, which is invested in engineering a more wear-resistant rocket slipper for its high-speed test track. This research uses a design of experiments approach to systematically identify and evaluate potential slipper attributes that mitigate wear according to a heat transfer model. Final findings include recommendations of slipper materials that theoretically perform similar to or better than the baseline Vascomax®C300 maraging steel material. …


Predictability Of Missing Data Theory To Improve U.S. Estimator’S Unreliable Data Problem, Tomeka S. Williams Jan 2021

Predictability Of Missing Data Theory To Improve U.S. Estimator’S Unreliable Data Problem, Tomeka S. Williams

Walden Dissertations and Doctoral Studies

Since the topic of improving data quality has not been addressed for the U.S. defense cost estimating discipline beyond changes in public policy, the goal of the study was to close this gap and provide empirical evidence that supports expanding options to improve software cost estimation data matrices for U.S. defense cost estimators. The purpose of this quantitative study was to test and measure the level of predictive accuracy of missing data theory techniques that were referenced as traditional approaches in the literature, compare each theories’ results to a complete data matrix used in support of the U.S. defense cost …


Tuning Optimization Software Parameters For Mixed Integer Programming Problems, Toni P. Sorrell Jan 2017

Tuning Optimization Software Parameters For Mixed Integer Programming Problems, Toni P. Sorrell

Theses and Dissertations

The tuning of optimization software is of key interest to researchers solving mixed integer programming (MIP) problems. The efficiency of the optimization software can be greatly impacted by the solver’s parameter settings and the structure of the MIP. A designed experiment approach is used to fit a statistical model that would suggest settings of the parameters that provided the largest reduction in the primal integral metric. Tuning exemplars of six and 59 factors (parameters) of optimization software, experimentation takes place on three classes of MIPs: survivable fixed telecommunication network design, a formulation of the support vector machine with the ramp …


Empirical Evaluation Of Different Features Of Design In Confirmatory Factor Analysis, Deyab Almaleki Apr 2016

Empirical Evaluation Of Different Features Of Design In Confirmatory Factor Analysis, Deyab Almaleki

Dissertations

Factor analysis (FA) is the study of variance within a group. Within-subject variance (WSV) is affected by multiple features in a study context, such as: the study experimental design (ED) and sampling design (SD), thus anything that influences or changes variance may affect the conclusions related to FA.

The aim of this study was to provide empirical evaluation of the influence of different aspects of ED and SD on WSV in the context of FA in terms of model precision and model estimate stability. Four Monte Carlo population correlation matrices were hypothesized based on different communality magnitudes (high, moderate, low, …


An Integrated Screening And Optimization Strategy, Nathaniel Jackson Rohbock Jul 2012

An Integrated Screening And Optimization Strategy, Nathaniel Jackson Rohbock

Theses and Dissertations

Within statistical methods, design of experiments (DOE) is well suited to make good inference from a minimal amount of data. Two types of designs within DOE are screening designs and optimization designs. Traditionally, these approaches have been necessarily separated by a gap between the objectives of each design and the methods available. Despite being so separated, in practice these designs are frequently connected by sequential experimentation. In fact, from the genesis of a project, the experimentor often knows that both designs will be necessary to accomplish his objectives. Due to advances in the understanding of experimental designs with complex aliasing …


Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar Jan 2011

Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar

Legacy Theses & Dissertations (2009 - 2024)

The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner.


Optimal Row-Column Designs For Correlated Errors And Nested Row-Column Designs For Uncorrelated Errors, Nizam Uddin Apr 1989

Optimal Row-Column Designs For Correlated Errors And Nested Row-Column Designs For Uncorrelated Errors, Nizam Uddin

Mathematics & Statistics Theses & Dissertations

In this dissertation the design problems are considered in the row-column setting for second order autonormal errors when the treatment effects are estimated by generalized least squares, and in the nested row-column setting for uncorrelated errors when the treatment effects are estimated by ordinary least squares. In the former case, universal optimality conditions are derived separately for designs in the plane and on the torus using more general linear models than those considered elsewhere in the literature. Examples of universally optimum planar designs are given, and a method is developed for the construction of optimum and near optimum designs, that …


Data Analysis Using Experimental Design Model Factorial Analysis Of Variance/Covariance (Dmaovc.Bas), Wesley E. Newton May 1985

Data Analysis Using Experimental Design Model Factorial Analysis Of Variance/Covariance (Dmaovc.Bas), Wesley E. Newton

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

DMAOVC.BAS is a computer program written in the compiler version of microsoft basic which performs factorial analysis of variance/covariance with expected mean squares. The program accommodates factorial and other hierarchical experimental designs with balanced sets of data. The program is writ ten for use on most modest sized microprocessors, in which the compiler is available. The program is parameter file driven where the parameter file consists of the response variable structure, the experimental design model expressed in a similar structure as seen in most textbooks, information concerning the factors (i.e. fixed or random, and the number of levels), and necessary …


Fortran Programs For The Calculation Of Most Of The Commonly Used Experimental Design Models, H. Wain Greenhalgh May 1967

Fortran Programs For The Calculation Of Most Of The Commonly Used Experimental Design Models, H. Wain Greenhalgh

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Two computer programs were developed using a CDC 3100. They were written in FORTRAN IV.

One program uses four tape drives, one card reader, and one printer. It will calculate factorial analysis of variance with or without covariance and/or multivariate analysis for one to eight factors and up to twenty-five variables.

The other program is used for completely randomized designs, randomized block designs, and latin square designs. It will handle twenty-five treatments, rows (blocks), and columns. The program can handle fifteen variables using any number of these variables for covariates.