Statistics and Probability Commons^™

Comparison Of Roadside Crash Injury Metrics Using Event Data Recorders, Doug Gabauer, Hampton C. Gabler

Faculty Journal Articles

The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk …

Realized Volatility Uncertainty, David E. Allen, Michael Mcaleer, Marcel Scharth

Research outputs pre 2011

The presence of high and time-varying volatility of volatility and leverage effects bring additional uncertainty in the tails of the distribution of asset returns, even though returns standardized by (ex-post) quadratic variation measures are nearly gaussian. We argue that in this setting modeling shocks to volatility is more relevant for applications than extracting more precise predictions of the variable, as point forecasts differences are swamped by the size of the volatility of volatility and rendered less informative by the nongaussianity in the ex-ante distribution of returns. Using S&P 500 data, we document that this volatility of volatility is subject to …

Pathos: Pervasive At Home Sleep Monitoring, Ian Obermiller, Sheikh Iqbal Ahamed

Mathematics, Statistics and Computer Science Faculty Research and Publications

Sleeping disorders affect a large percentage of the population, and many of them go undiagnosed each year because the method of diagnosis is to stay overnight at a sleep center. Because pervasive technologies have become so prevalent and affordable, sleep monitoring is no longer confined to a permanent installation, and can therefore be brought directly into the user home. We present a unique solution to the problem of home sleep monitoring that has the possibility to take the place of and expand on the data from a sleep center. PATHOS focuses not only on analyzing patterns during the night, but …

Characterization Of Digraphs With Equal Domination Graphs And Underlying Graphs, Kim A. S. Factor, Larry J. Langley

Mathematics, Statistics and Computer Science Faculty Research and Publications

A domination graph of a digraph D , dom(D)dom(D), is created using the vertex set of D and edge {u,v}∈E[dom(D)]{u,v}∈E[dom(D)] whenever (u,z)∈A(D)(u,z)∈A(D) or (v,z)∈A(D)(v,z)∈A(D) for every other vertex z∈V(D)z∈V(D). The underlying graph of a digraph DD, UG(D)UG(D), is the graph for which D is a biorientation. We completely characterize digraphs whose underlying graphs are identical to their domination graphs, UG(D)=dom(D)UG(D)=dom(D). The maximum and minimum number of single arcs in these digraphs, and their characteristics, is given.

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.

On Matched Pairs Sign Test Using Bivariate Ranked Set Sampling: An Application To Environmental Issues, Hani M. Samawi, Mohammad F. Al-Saleh, Obaid Al-Saidy

Biostatistics: Faculty Publications

The matched pairs sign test using bivariate ranked set sampling (BVRSS) is introduced and investigated. We show that this test is asymptotically more efficient than its counterpart sign test based on a bivariate simple random sample (BVSRS). The asymptotic null distribution and the efficiency of the test are derived. The Pitman asymptotic relative efficiency is used to compare the asymptotic performance of the matched pairs sign test using BVRSS versus using BVSRS. For small sample sizes, the bootstrap method is used to estimate P-values. Numerical comparisons are used to gain insight about the efficiency of the BVRSS sign test compared …

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.

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 …

Data Mining Methods For Malware Detection, Muazzam Siddiqui

Electronic Theses and Dissertations

This research investigates the use of data mining methods for malware (malicious programs) detection and proposed a framework as an alternative to the traditional signature detection methods. The traditional approaches using signatures to detect malicious programs fails for the new and unknown malwares case, where signatures are not available. We present a data mining framework to detect malicious programs. We collected, analyzed and processed several thousand malicious and clean programs to find out the best features and build models that can classify a given program into a malware or a clean class. Our research is closely related to information retrieval …

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 …

Empirical Processes And Roc Curves With An Application To Linear Combinations Of Diagnostic Tests, Costel Chirila

University of Kentucky Doctoral Dissertations

The Receiver Operating Characteristic (ROC) curve is the plot of Sensitivity vs. 1- Specificity of a quantitative diagnostic test, for a wide range of cut-off points c. The empirical ROC curve is probably the most used nonparametric estimator of the ROC curve. The asymptotic properties of this estimator were first developed by Hsieh and Turnbull (1996) based on strong approximations for quantile processes. Jensen et al. (2000) provided a general method to obtain regional confidence bands for the empirical ROC curve, based on its asymptotic distribution.

Since most biomarkers do not have high enough sensitivity and specificity to …

Evidence Contrary To The Statistical View Of Boosting, David Mease, A. Wyner

Faculty Publications

The statistical perspective on boosting algorithms focuses on optimization, drawing parallels with maximum likelihood estimation for logistic regression. In this paper we present empirical evidence that raises questions about this view. Although the statistical perspective provides a theoretical framework within which it is possible to derive theorems and create new algorithms in general contexts, we show that there remain many unanswered important questions. Furthermore, we provide examples that reveal crucial flaws in the many practical suggestions and new methods that are derived from the statistical view. We perform carefully designed experiments using simple simulation models to illustrate some of these …

Statistical Issues In The Normalization Of Multi-Species Microarray Data, John R. Stevens, Balasubramanian Ganesan, Prerak Desai, Sweta Rajan, Bart C. Weimer

Mathematics and Statistics Faculty Publications

Several species of bacteria are involved in the production of cheese, including Lactobacillus brevis and Lactococcus lactis. A custom-designed Affymetrix microarray was recently developed to study gene expression in three organisms on a single chip. This array contains only perfect match features for the coding and non-coding regions in the genomes of all three sequences. The multi-species nature of this array version raises interesting questions regarding the preprocessing or normalization strategies for the analysis of gene expression data. We present and evaluate several possible strategies using both cDNA dilution data and experimental expression data from a repeated measures design. …

Probe Level Analysis Of Affymetrix Microarray Data, Richard Ellis Kennedy

Theses and Dissertations

The analysis of Affymetrix GeneChip® data is a complex, multistep process. Most often, methodscondense the multiple probe level intensities into single probeset level measures (such as RobustMulti-chip Average (RMA), dChip and Microarray Suite version 5.0 (MAS5)), which are thenfollowed by application of statistical tests to determine which genes are differentially expressed. An alternative approach is a probe-level analysis, which tests for differential expression directly using the probe-level data. Probe-level models offer the potential advantage of more accurately capturing sources of variation in microarray experiments. However, this has not been thoroughly investigated, since current research efforts have largely focused on the …

Benford And Your Taxes, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

Nothing is certain but death and taxes, they say. On the death front, we are making some inroads with all our medical marvels, at least in postponing it if not actually avoiding it. But when it comes to taxes, we have no defense other than a bit of creativity in our tax returns.

Tests For Correlation On Bivariate Nonnormal Distributions, Louanne Margaret Beversdorf

UNF Graduate Theses and Dissertations

Many samples in the real world are very small in size and often do not follow a normal distribution. Existing tests for correlation have restrictions on the distribution of data and sample sizes, therefore the current tests cannot be used in some real world situations.

In this thesis, two tests are considered to test hypotheses about the population correlation coefficient. The tests are based on statistics transformed by a saddlepoint approximation and by Fisher's Z-transformation. The tests are conducted on small samples of bivariate nonnormal data and found to perfom well.

Simulations were run in order to compare the type …