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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
open access

Call Option Premium Dynamics

Description: This study has a twofold purpose: to demonstrate the use of the Marquardt compromise method in estimating the unknown parameters contained in the probability call-option pricing models and to test empirically the following models: the Boness, the Black-Scholes, the Merton proportional dividend, the Ingersoll differential tax, and the Ingersoll proportional dividend and differential tax.
Date: December 1982
Creator: Chen, Jim
Partner: UNT Libraries
open access

Financial Leverage and the Cost of Capital

Description: The objective of the research reported in this dissertation is to conduct an empirical test of the hypothesis that, excluding income tax effects, the cost of capital to a firm is independent of the degree of financial leverage employed by the firm. This hypothesis, set forth by Franco Modigliani and Merton Miller in 1958, represents a challenge to the traditional view on the subject, a challenge which carries implications of considerable importance in the field of finance. The challenge has led… more
Date: December 1977
Creator: Brust, Melvin F.
Partner: UNT Libraries
open access

Validation and Investigation of the Four Aspects of Cycle Regression: A New Algorithm for Extracting Cycles

Description: The cycle regression analysis algorithm is the most recent addition to a group of techniques developed to detect "hidden periodicities." This dissertation investigates four major aspects of the algorithm. The objectives of this research are 1. To develop an objective method of obtaining an initial estimate of the cycle period? the present procedure of obtaining this estimate involves considerable subjective judgment; 2. To validate the algorithm's success in extracting cycles from multi-cylical… more
Date: December 1982
Creator: Mehta, Mayur Ravishanker
Partner: UNT Libraries
open access

The Normal Curve Approximation to the Hypergeometric Probability Distribution

Description: The classical normal curve approximation to cumulative hypergeometric probabilities requires that the standard deviation of the hypergeometric distribution be larger than three which limits the usefulness of the approximation for small populations. The purposes of this study are to develop clearly-defined rules which specify when the normal curve approximation to the cumulative hypergeometric probability distribution may be successfully utilized and to determine where maximum absolute differenc… more
Date: December 1981
Creator: Willman, Edward N. (Edward Nicholas)
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

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

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

Impact of Forecasting Method Selection and Information Sharing on Supply Chain Performance.

Description: Effective supply chain management gains much attention from industry and academia because it helps firms across a supply chain to reduce cost and improve customer service level efficiently. Focusing on one of the key challenges of the supply chains, namely, demand uncertainty, this dissertation extends the work of Zhao, Xie, and Leung so as to examine the effects of forecasting method selection coupled with information sharing on supply chain performance in a dynamic business environment. The r… more
Date: December 2009
Creator: Pan, Youqin
Partner: UNT Libraries
open access

Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers

Description: In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are two text data computer algorithms that have received much attention individually… more
Date: December 2011
Creator: Anaya, Leticia H.
Partner: UNT Libraries
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