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Mathematical Programming Approaches to the Three-Group Classification Problem

Description: In the last twelve years there has been considerable research interest in mathematical programming approaches to the statistical classification problem, primarily because they are not based on the assumptions of the parametric methods (Fisher's linear discriminant function, Smith's quadratic discriminant function) for optimality. This dissertation focuses on the development of mathematical programming models for the three-group classification problem and examines the computational efficiency an… more
Date: August 1993
Creator: Loucopoulos, Constantine
Partner: UNT Libraries
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A Simulation Study Comparing Various Confidence Intervals for the Mean of Voucher Populations in Accounting

Description: This research examined the performance of three parametric methods for confidence intervals: the classical, the Bonferroni, and the bootstrap-t method, as applied to estimating the mean of voucher populations in accounting. Usually auditing populations do not follow standard models. The population for accounting audits generally is a nonstandard mixture distribution in which the audit data set contains a large number of zero values and a comparatively small number of nonzero errors. This study … more
Date: December 1992
Creator: Lee, Ihn Shik
Partner: UNT Libraries
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Derivation of Probability Density Functions for the Relative Differences in the Standard and Poor's 100 Stock Index Over Various Intervals of Time

Description: In this study a two-part mixed probability density function was derived which described the relative changes in the Standard and Poor's 100 Stock Index over various intervals of time. The density function is a mixture of two different halves of normal distributions. Optimal values for the standard deviations for the two halves and the mean are given. Also, a general form of the function is given which uses linear regression models to estimate the standard deviations and the means. The density … more
Date: August 1988
Creator: Bunger, R. C. (Robert Charles)
Partner: UNT Libraries
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Robustness of Parametric and Nonparametric Tests When Distances between Points Change on an Ordinal Measurement Scale

Description: The purpose of this research was to evaluate the effect on parametric and nonparametric tests using ordinal data when the distances between points changed on the measurement scale. The research examined the performance of Type I and Type II error rates using selected parametric and nonparametric tests.
Date: August 1994
Creator: Chen, Andrew H. (Andrew Hwa-Fen)
Partner: UNT Libraries
open access

Robustness of the One-Sample Kolmogorov Test to Sampling from a Finite Discrete Population

Description: One of the most useful and best known goodness of fit test is the Kolmogorov one-sample test. The assumptions for the Kolmogorov (one-sample test) test are: 1. A random sample; 2. A continuous random variable; 3. F(x) is a completely specified hypothesized cumulative distribution function. The Kolmogorov one-sample test has a wide range of applications. Knowing the effect fromusing the test when an assumption is not met is of practical importance. The purpose of this research is to analyze the … more
Date: December 1996
Creator: Tucker, Joanne M. (Joanne Morris)
Partner: UNT Libraries
open access

Comparing the Powers of Several Proposed Tests for Testing the Equality of the Means of Two Populations When Some Data Are Missing

Description: In comparing the means .of two normally distributed populations with unknown variance, two tests very often used are: the two independent sample and the paired sample t tests. There is a possible gain in the power of the significance test by using the paired sample design instead of the two independent samples design.
Date: May 1994
Creator: Dunu, Emeka Samuel
Partner: UNT Libraries
open access

Classification by Neural Network and Statistical Models in Tandem: Does Integration Enhance Performance?

Description: The major purposes of the current research are twofold. The first purpose is to present a composite approach to the general classification problem by using outputs from various parametric statistical procedures and neural networks. The second purpose is to compare several parametric and neural network models on a transportation planning related classification problem and five simulated classification problems.
Date: December 1998
Creator: Mitchell, David
Partner: UNT Libraries
open access

The Effect of Certain Modifications to Mathematical Programming Models for the Two-Group Classification Problem

Description: This research examines certain modifications of the mathematical programming models to improve their classificatory performance. These modifications involve the inclusion of second-order terms and secondary goals in mathematical programming models. A Monte Carlo simulation study is conducted to investigate the performance of two standard parametric models and various mathematical programming models, including the MSD (minimize sum of deviations) model, the MIP (mixed integer programming) model … more
Date: May 1994
Creator: Wanarat, Pradit
Partner: UNT Libraries
open access

A Heuristic Procedure for Specifying Parameters in Neural Network Models for Shewhart X-bar Control Chart Applications

Description: This study develops a heuristic procedure for specifying parameters for a neural network configuration (learning rate, momentum, and the number of neurons in a single hidden layer) in Shewhart X-bar control chart applications. Also, this study examines the replicability of the neural network solution when the neural network is retrained several times with different initial weights.
Date: December 1993
Creator: Nam, Kyungdoo T.
Partner: UNT Libraries
open access

The Fixed v. Variable Sampling Interval Shewhart X-Bar Control Chart in the Presence of Positively Autocorrelated Data

Description: This study uses simulation to examine differences between fixed sampling interval (FSI) and variable sampling interval (VSI) Shewhart X-bar control charts for processes that produce positively autocorrelated data. The influence of sample size (1 and 5), autocorrelation parameter, shift in process mean, and length of time between samples is investigated by comparing average time (ATS) and average number of samples (ANSS) to produce an out of control signal for FSI and VSI Shewhart X-bar charts. … more
Date: May 1993
Creator: Harvey, Martha M. (Martha Mattern)
Partner: UNT Libraries
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