Digital Commons Network^™

Optimal Stopping And Free Boundary Characterizations For Some Brownian Control Problems, Amarjit Budhiraja, Kevin J. Ross

Statistics

A singular stochastic control problem with state constraints in twodimensions is studied. We show that the value function is C1 and its directional derivatives are the value functions of certain optimal stopping problems. Guided by the optimal stopping problem, we then introduce the associated no-action region and the free boundary and show that, under appropriate conditions, an optimally controlled process is a Brownian motion in the noaction region with reflection at the free boundary. This proves a conjecture of Martins, Shreve and Soner [SIAM J. Control Optim. 34 (1996) 2133–2171] on the form of an optimal control for this class …

Property Of Kelley For The Cartesian Products And Hyperspaces, W. J. Charatonik, J. J. Charatonik

Mathematics and Statistics Faculty Research & Creative Works

A continuum X having the property of Kelley is constructed such that neither X × [0, 1], nor the hyperspace C(X), nor small Whitney levels in C(X) have the property of Kelley. This answers several questions asked in the literature.

Iterated Oscillation Criteria For Delay Dynamic Equations Of First Order, B. Karpuz, O. Öcalan, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

We obtain new sufficient conditions for the oscillation of all solutions of first-order delay dynamic equations on arbitrary time scales, hence combining and extending results for corresponding differential and difference equations. Examples, some of which coincide with well-known results on particular time scales, are provided to illustrate the applicability of our results.

Maximum Likelihood Estimation Methodology Comparison For The Three-Parameter Weibull Distribution With Applications To Offshore Oil Spills In The Gulf Of Mexico, William V. Harper, Thomas R. James, Ted G. Eschenbach, Leigh Slauson

Mathematics Faculty Scholarship

Maximum Likelihood estimation of the two-parameter Weibull distribution is straightforward; however, there are multiple methods for maximum likelihood estimation of the three-parameter Weibull. This paper presents an evaluation of these methods using four data sets including oil spill data from the Gulf of Mexico. Highlighted are fairly major differences in the estimated parameters between nine statistical packages. A VBA routine has been developed allowing practitioners to implement three-parameter Weibull maximum likelihood estimate within Excel. The code and support documentation are available free at http:faculty.otterbein.edu/WHarper.

Application Of The Probability Distribution Of Distances In A Layered Sphere To Electrostatic Energy, Neal Livesay

Theses & Honors Papers

This thesis works on a problem that involves calculating the total electrostatic interaction energy of two charged particles uniformly distributed in a sphere. It determines that traditional methods and the use of probability techniques yield equivalent results for the electrostatic energy in a charged layered sphere.

Evaluation Of Serotonin As A Feedback Inhibitor Of Lactation In The Bovine, L. L. Hernandez, C. M. Stiening, J. B. Wheelock, L. H. Baumgard, Anne M. Parkhurst, R. J. Collier

Department of Statistics: Faculty Publications

Serotonin (5-HT), a neurotransmitter synthesized from tryptophan, has been proposed as a feedback inhibitor of lactation. We determined that the gene coding for tryptophan hydroxylase 1, the rate-limiting enzyme for 5-HT synthesis, is expressed in bovine mammary epithelial cells in vitro and is upregulated by prolactin. In addition, 5-HT reduced the expression of α-lactalbumin and casein genes in vitro. Furthermore, inhibiting 5-HT synthesis with p-chlorophenylalanine or blocking the 5-HT receptor with methysergide (METH) increased milk protein gene expression. We then evaluated effects of intramammary 5-HT or METH infusion on production and milk composition in 6 multiparous Holstein cows. Cows …

J. K. Ghosh’S Contribution To Statistics: A Brief Outline, Bertrand Clarke, Subhashis Ghosal

Department of Statistics: Faculty Publications

Professor Jayanta Kumar Ghosh has contributed massively to various areas of Statistics over the last five decades. Here, we survey some of his most important contributions. In roughly chronological order, we discuss his major results in the areas of sequential analysis, foundations, asymptotics, and Bayesian inference. It is seen that he progressed from thinking about data points, to thinking about data summarization, to the limiting cases of data summarization in as they relate to parameter estimation, and then to more general aspects of modeling including prior and model selection.

An Ensemble Approach To Improved Prediction From Multitype Data, Jennifer Clarke

Department of Statistics: Faculty Publications

We have developed a strategy for the analysis of newly available binary data to improve outcome predictions based on existing data (binary or non-binary). Our strategy involves two modeling approaches for the newly available data, one combining binary covariate selection via LASSO with logistic regression and one based on logic trees. The results of these models are then compared to the results of a model based on existing data with the objective of combining model results to achieve the most accurate predictions. The combination of model predictions is aided by the use of support vector machines to identify subspaces of …

A Bayesian Test For Excess Zeros In A Zero-Inflated Power Series Distribution, Archan Bhattacharya, Bertrand S. Clarke, Gauri S. Datta

Department of Statistics: Faculty Publications

Power series distributions form a useful subclass of one-parameter discrete exponential families suitable for modeling count data. A zero-inflated power series distribution is a mixture of a power series distribution and a degenerate distribution at zero, with a mixing probability p for the degenerate distribution. This distribution is useful for modeling count data that may have extra zeros. One question is whether the mixture model can be reduced to the power series portion, corresponding to p = 0, or whether there are so many zeros in the data that zero inflation relative to the pure power series distribution must be …

On The Asymptotic Integration Of Nonlinear Dynamic Equations, Elvan Akin, Smail Djebali, Toufik Moussaoui, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

The purpose of this paper is to study the existence and asymptotic behavior of solutions to a class of second-order nonlinear dynamic equations on unbounded time scales. Four different results are obtained by using the Banach fixed point theorem, the Boyd and Wong fixed point theorem, the Leray-Schauder nonlinear alternative, and the Schauder fixed point theorem. For each theorem, an illustrative example is presented. The results provide unification and some extensions in the time scale setup of the theory of asymptotic integration of nonlinear equations both in the continuous and discrete cases

Transition To Turbulence, Small Disturbances, And Sensitivity Analysis Ii: The Navier-Stokes Equations, John R. Singler

Mathematics and Statistics Faculty Research & Creative Works

Recent research has shown that small disturbances in the linearized Navier-Stokes equations cause large energy growth in solutions. Although many researchers believe that this interaction triggers transition to turbulence in flow systems, the role of the nonlinearity in this process has not been thoroughly investigated. This paper is the second of a two part work in which sensitivity analysis is used to study the effects of small disturbances on the transition process. In the first part, sensitivity analysis was used to predict the effects of a small disturbance on solutions of a motivating problem, a highly sensitive one dimensional Burgers' …

Transition To Turbulence, Small Disturbances, And Sensitivity Analysis I: A Motivating Problem, John R. Singler

Mathematics and Statistics Faculty Research & Creative Works

For over 100 years, researchers have attempted to predict transition to turbulence in fluid flows by analyzing the spectrum of the linearized Navier-Stokes equations. However, for many simple flows this approach fails to match experimental results. Recently, new scenarios for transition have been proposed that are based on the interaction of the linearized equations of motion with small disturbances to the flow system. These new "mostly linear" theories have increased our understanding of the transition process, but the role of nonlinearity has not been explored in detail. This paper is the first of a two part work in which sensitivity …

Ua56/1 Fact Book, Wku Institutional Research

WKU Administration Documents

Statistical and demographic profile of WKU.

An Improved String Composition Method For Sequence Comparison, Guoqing Lu, Shunpu Zhang, Xiang Fang

Department of Statistics: Faculty Publications

Background: Historically, two categories of computational algorithms (alignment-based and alignment-free) have been applied to sequence comparison–one of the most fundamental issues in bioinformatics. Multiple sequence alignment, although dominantly used by biologists, possesses both fundamental as well as computational limitations. Consequently, alignment-free methods have been explored as important alternatives in estimating sequence similarity. Of the alignment-free methods, the string composition vector (CV) methods, which use the frequencies of nucleotide or amino acid strings to represent sequence information, show promising results in genome sequence comparison of prokaryotes. The existing CV-based methods, however, suffer certain statistical problems, thereby underestimating the amount of evolutionary …

Peridocity, Change Detection And Prediction In Microarrays, Mohammad Shahidul Islam

Digitized Theses

Three topics in the analysis of microarray genomic data are discussed and improved statistical methods are developed in each case. A statistical test with higher power is developed for detecting periodicity in microarray time series data. Periodicity in short series, with non-Fourier frequencies, is detected through a Pearson curve calibrated to the null distribution obtained by computer simulation. Unlike other traditional methods, this approach is applicable even in the presence of missing values or unequal time intervals. The usefulness of the new method is demonstrated on simulated series as well as actual microarray time series.

The second topic develops a …

Why Divide By (N-1) For Sample Standard Deviation?, Paul Savory

Department of Industrial and Management Systems Engineering: Instructional Materials

In statistics, the sample standard deviation is a widely used measure of the variability or dispersion of a data set. The standard deviation of a data set is the square root of its variance. In calculating the sample standard deviation, the divisor is the number of samples in the data set minus one (n-1) rather than n. This often confuses students. This paper offers a quick overview of why the divisor is (n-1) for calculating the sample standard deviation.

Octahedral Dice, Todd Estroff, Jeremiah Farrell

Scholarship and Professional Work - LAS

All five Platonic solids have been used as random number generators in games involving chance with the cube being the most popular. Martin Gardenr, in his article on dice (MG 1977) remarks: "Why cubical?... It is the easiest to make, its six sides accomodate a set of numbers neither too large nor too small, and it rolls easily enough but not too easily."

Gardner adds that the octahedron has been the next most popular as a randomizer. We offer here several problems and games using octahedral dice. The first two are extensions from Gardner's article. All answers will be given …

Professor Gopal Kanji's Retirement As Editor Of Journal Of Applied Statistics, M. C. Agrawal, Steven B. Caudill, S. Chakraborti, Norman Draper, Ian Dryden, Joe Gani, Steven G. Gilmour, Z. Govindarajulu, David J. Hand, Dayanand Naik

Mathematics & Statistics Faculty Publications

(First paragraph) This. issue of Journal of Applied Statistics marks the first in its history which does not fall under the editorship of its founder Professor Gopal Kanji. Following his retirement from the role we would like to use this editorial to outline the history and development of the Journal and pay tribute to the many achievements of Gopal’s career.

Changes In Poverty And Educational Attainment, 2000 To 2007 Poverty Rates Increasing For Those With College Education, Too, Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Hispanics And Asians Increase In Numbers In Cuyahoga County An Analysis Of 2007 County Population Estimates, Mark Salling

All Maxine Goodman Levin School of Urban Affairs Publications

No abstract provided.

Mathematical Analysis Of The Transmission Dynamics Of Hiv/Tb Coinfection In The Presence Of Treatment, Oluwaseun Sharomi, Chandra N. Podder, Abba B. Gumel, Baojun Song

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

This paper addresses the synergistic interaction between HIV and mycobacterium tuberculosis using a deterministic model, which incorporates many of the essential biological and epidemiological features of the two diseases. In the absence of TB infection, the model (IIIV-only model) is shown to have a globally asymptotically stable, disease-free equilibrium whenever the associated reproduction number is less than unity and has a unique endemic equilibrium whenever this number exceeds unity. On the other hand, the model with TB alone (TB-only model) undergoes the phenomenon of backward bifurcation, where the stable disease-free equilibrium co-exists with a stable endemic equilibrium when the associated …

How Do You Interpret A Confidence Interval?, Paul Savory

Department of Industrial and Management Systems Engineering: Instructional Materials

A confidence interval (CI) is an interval estimate of a population parameter. Instead of estimating the parameter by a single value, a point estimate, an interval likely to cover the parameter is developed. Many student incorrectly interpret the meaning of a confidence interval. This paper offers a quick overview of how to correctly interpret a confidence interval.

A Comparison Of Different Methods For Predicting Cancer Mortality Counts At The State Level, Corinne Wilson

Virginia Journal of Science

Cancer is a major health issue in the United States. Reliable estimates of yearly cancer mortality counts are essential for resourcing and planning. The American Cancer Society has used several methods of forecasting to estimate the future cancer burden and researchers are continually working to develop new methods with improved performance. There have been studies comparing different models for predicting the US cancer mortality counts. This study explores and compares several different models for cancer mortality count predictions at the state level, principally for the state of Virginia. Results of the comparisons appear to show the final improved model to …

The Third Generation Acd Model : A Semiparametric Approach, Pipat Wongsaart, Jiti Gao, David E. Allen

Research outputs pre 2011

Having concluded that thus far the question about the most appropriate type of nonlinear ACD model has not been satisfactorily answered, we intend to develop a novel ACD modelling methodology based on an iterative estimation algorithm and a semiparametric autoregressive process that not only allows the data to speak for itself, but also is robust across datasets without relying on some computational factors, such as the hypothesis about the probability density function of the standardised durations. We propose in this paper the Semiparametric ACD (SP-ACD) model, which can be considered a starting point of such a development. To address the …

Monaco/Mavric Evaluation For Facility Shielding And Dose Rate Analysis, Charlotta Sanders, Denis Beller

Reactor Campaign (TRP)

The dimensions and the large amount of shielding required for Global Nuclear Energy Partnership (GNEP) facilities, advanced radiation shielding, and dose computation techniques are beyond today’s capabilities and will certainly be required. With the Generation IV Nuclear Energy System Initiative, it will become increasingly important to be able to accurately model advanced Boiling Water Reactor and Pressurized Water Reactor facilities, and to calculate dose rates at all locations within a containment (e.g., resulting from radiations from the reactor as well as the from the primary coolant loop) and adjoining structures (e.g., from the spent fuel pool).

The MAVRIC sequence is …

Application Of The Fractal Market Hypothesis For Modelling Macroeconomic Time Series, Jonathan Blackledge

Articles

This paper explores the conceptual background to financial time series analysis and financial signal processing in terms of the Efficient Market Hypothesis. By revisiting the principal conventional approaches to market analysis and the reasoning associated with them, we develop a Fractal Market Hypothesis that is based on the application of non-stationary fractional dynamics using an operator of the type
∂² / ∂x² − σ^q(t) * ∂ ^q(t)/ ∂t^q(t)

where σ⁻¹ is the fractional diffusivity and q is the Fourier dimension which, for the topology considered, (i.e. the one-dimensional case) is related to the Fractal …

Length Bias In The Measurements Of Carbon Nanotubes, Paul H. Kvam

Department of Math & Statistics Faculty Publications

To measure carbon nanotube lengths, atomic force microscopy and special software are used to identify and measure nanotubes on a square grid. Current practice does not include nanotubes that cross the grid, and, as a result, the sample is length-biased. The selection bias model can be demonstrated through Buffon’s needle problem, extended to general curves that more realistically represent the shape of nanotubes observed on a grid. In this article, the nonparametric maximum likelihood estimator is constructed for the length distribution of the nanotubes, and the consequences of the length bias are examined. Probability plots reveal that the corrected length …

Degradation Models, Suk Joo Bae, Paul H. Kvam

Department of Math & Statistics Faculty Publications

Reliability testing typically generates product lifetime data, but for some tests, covariate information about the wear and tear on the product during the life test can provide additional insight into the product’s lifetime distribution. This usage, or degradation, can be the physical parameters of the product (e.g., corrosion thickness on a metal plate) or merely indicated through product performance (e.g., the luminosity of a light emitting diode). The measurements made across the product’s lifetime are degradation data, and degradation analysis is the statistical tool for providing inference about the lifetime distribution from the degradation data.

Load Sharing Models, Paul H. Kvam, Jye-Chyi Lu

Department of Math & Statistics Faculty Publications

Consider a system of components whose lifetimes are governed by a probability distribution. Load sharing refers to a model of stochastic interdependency between components that operate within a system. If components are set up in a parallel system (see Parallel, Series, and Series–Parallel Systems) for example, the system survives as long as at least one component is operating. In a typical load-sharing system, once a component fails, the remaining components suffer an increase in failure rate due to the extra “load” they must encumber due to the failed component.

Empirical Bayes And Hierarchical Bayes Estimation Of Skew Normal Populations, Naveen K. Bansal, Mehdi Maadooliat, Xiaowei Wang

Mathematics, Statistics and Computer Science Faculty Research and Publications

We develop empirical and hierarchical Bayesian methodologies for the skew normal populations through the EM algorithm and the Gibbs sampler. A general concept of skewness to the normal distribution is considered throughout. Motivations are given for considering the skew normal population in applications, and an example is presented to demonstrate why the skew normal distribution is more applicable than the normal distribution for certain applications.