Ua56/1 Fact Book,
2010
Western Kentucky University
Ua56/1 Fact Book, Wku Institutional Research
WKU Administration Documents
Statistical and demographic profile of WKU.
Is Screening Cargo Containers For Smuggled Nuclear Threats Worthwhile?,
2010
Virginia Commonwealth University
Is Screening Cargo Containers For Smuggled Nuclear Threats Worthwhile?, Jason R. W. Merrick, Laura A. Mclay
Statistical Sciences and Operations Research Publications
In recent years, Customs and Border Protection (CBP) has installed radiation sensors to screen cargo containers entering theUnited States. They are concerned that terrorists could use containers to smuggle radiological material into the country and carry out attacks with dirty bombs or a nuclear device. Recent studies have questioned the value of improving this screening system with new sensor technology. The cost of delays caused by frequent false alarms outweighs any reduction in the probability of an attack in an expected cost analysis. We extend existing methodology in three ways to demonstrate how additional factors affect the value of screening …
Type Ii Robustness Of The Null Hypothesis Rho = 0 For Non-Normal Distributions,
2010
Wayne State University
Type Ii Robustness Of The Null Hypothesis Rho = 0 For Non-Normal Distributions, Stephanie Wren
Wayne State University Dissertations
Is the t test statistic for the Pearson Product Moment Correlation Coefficient robust to errors of the second kind? This investigation indirectly measured the effects of power through a type 2 error rate robustness study. The results were revealing.
Identification Of Neuroblastoma And Its Prognostic Markers Using Raman Spectroscopy,
2010
Wayne State University
Identification Of Neuroblastoma And Its Prognostic Markers Using Raman Spectroscopy, Rachel Kast
Wayne State University Dissertations
Introduction: Neuroblastoma is the most common cancer of infancy. It is one of several peripheral nervous system tumors, including ganglioneuroma, peripheral nerve sheath tumor, and pheochromocytoma. It is commonly situated on the adrenal gland. It displays similar histology to other small round blue cell tumors, including non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma. One method of judging neuroblastoma aggressiveness uses tumor histology factors, including mitosis-karyorrhexis index, Schwannian stromal development, degree of differentiation, and patient age. Tumor aggressiveness can also be judged based on the amplification of certain genes, including MYCN. Raman spectroscopy is a physics-based method which identifies the biochemical …
Traveling Wave Solutions For A Nonlocal Reaction-Diffusion Model Of Influenza A Drift,
2010
Wright State University - Main Campus
Traveling Wave Solutions For A Nonlocal Reaction-Diffusion Model Of Influenza A Drift, Joaquin Riviera, Yi Li
Mathematics and Statistics Faculty Publications
In this paper we discuss the existence of traveling wave solutions for a nonlocal reaction-diffusion model of Influenza A proposed in Lin et. al. (2003). The proof for the existence of the traveling wave takes advantage of the different time scales between the evolution of the disease and the progress of the disease in the population. Under this framework we are able to use the techniques from geometric singular perturbation theory to prove the existence of the traveling wave.
Simulating Power For One-Way Anova By Using Non-Normal Error Distributions,
2010
Utah State University
Simulating Power For One-Way Anova By Using Non-Normal Error Distributions, Caixia Xu
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Usually we assume that the distribution of the additive errors in a one-way ANOVA linear model is normal. However, exceptions to this assumption about the error distribution may exist. In such cases, we might consider non-normal error distributions, but proceed with the "usual" ANOVA F-test analyses. This study focuses on simulating power for one-way ANOVA when using non-normal error distributions.
Bayesian Nonparametric Regression With A Flexible Error Term Distribution,
2010
University of Texas at El Paso
Bayesian Nonparametric Regression With A Flexible Error Term Distribution, Courtney Marie Barnes
Open Access Theses & Dissertations
Datasets often exhibit heavy tailed behavior and standard analyses are often heavily influenced by outliers. We propose a nonparametric regression model whose error term distribution is a mixture of a normal and a Student t distribution. This results in a model that is more resistant to outliers compared to a model with a normal error term.
Identifying Influential Observations Through The Intraclass Correlation Coefficient,
2010
University of Texas at El Paso
Identifying Influential Observations Through The Intraclass Correlation Coefficient, Angel De Jesus Davalos
Open Access Theses & Dissertations
In this thesis, we analyze the performance of adapting the DFBETA statistic for identifying influential observations on the intraclass correlation coefficient under the assumptions of the one-way random effects model. Additionally, we introduce an approach for transforming negative intraclass correlation coefficient estimation values using the method of moments estimator. We apply this method on a data set of repeated blood pressure measurements, after which we will investigate implications of identifying influential observations.
Detecting Outliers And Influential Observations In Survival Model.,
2010
Universiti Malaya
Detecting Outliers And Influential Observations In Survival Model., Nor Akmal Md Noh
Student Works (2010-2019)
This study proposes outlier and influential observation detection procedures for Cox proportional hazard model. In the estimation process, the parameters for Cox proportional hazard model are estimated using partial likelihood method, while the baseline hazard estimates are obtained using Nelson-Aalen method. The procedure of outlier detection is based on three types of residuals; deviance, log-odd and normal deviate residuals. We study their properties and compare their performance in detecting outliers via simulation. On the other hand, we propose a procedure of identifying influential observation using forward search method. The method has been shown to be effective in detecting influential observations …
Statistical Modelling And Inference For A Class Of Bivariate And Related Distributions.,
2010
Universiti Malaya
Statistical Modelling And Inference For A Class Of Bivariate And Related Distributions., Ng Choung Min
Student Works (2010-2019)
This thesis considers bivariate extension of the Meixner class of distributions by the method of generalized trivariate reduction so that the marginal distributions have different parameters; in particular, a new bivariate negative binomial (BNB) distribution is examined. Different marginal parameters allow flexibility in statistical modelling and simulation studies when different marginal distributions and a specified correlation are required. The multivariate extension of this class of distributions is also given. Specifically, various interesting properties of the proposed BNB distribution, such as canonical expansion and quadrant dependence are examined. In addition, potential applications of the proposed distribution, as a bivariate mixed Poisson …
Some Problems Of Outliers In Circular Data.,
2010
Universiti Malaya
Some Problems Of Outliers In Circular Data., Ali H.M. Abuzaid
Student Works (2010-2019)
This study considers three problems of outliers in circular statistics. The first problem is an attempt to use the standard outlier detection procedures for linear data set by approximating circular variables by linear variables. This is possible for large values of concentration parameter. Series of simulation studies are carried out to specify the accepted value of the concentration parameter so that the von Mises distribution can be approximated by normal distribution. The second is the problem of outliers in circular samples. Two numerical tests of discordancy are proposed to identify outliers. The test statistics are based on the summation of …
Anomalous Diffusion In Trading Models.,
2010
Universiti Malaya
Anomalous Diffusion In Trading Models., Sidiq Mohamad Khidzir
Student Works (2010-2019)
Econophysics is an interdisciplinary research field applying the mathematical methods of statistical physics to economics and finance. It emphasizes quantitative analysis of large amounts of economic and financial data as oppose to the more philosophical approach of political economics. A popular topic studied in econophysics is the distribution of wealth.Many models have been proposed to explain the trading dynamics [12,13] leading to the distribution of wealth universally observed in many countries. A more recent topic in econophysics is the movement of money studied by Brockmann in [19,20]. In this work, we are interested in studying the relation between the distribution …
Mixture Model Clustering For Very Large Data Sets.,
2010
Universiti Malaya
Mixture Model Clustering For Very Large Data Sets., Leong Siow Hoo
Student Works (2010-2019)
This thesis develops mixture model clustering algorithms scalable to data sets that do not fit into the computer memory buffer. Two algorithms, FlexClust and FlexClustMix, are proposed for clustering very large continuous and mixed data sets respectively. The basic framework of the algorithms is to scale down data incrementally using data compression, and incorporates the later compressed data into the current model with the ability to recover new clusters that have been missed out in the earlier compressed data. It consists of three modules: 1) incremental compression, 2) detecting change in cluster structure, and 3) update of current model. In …
Confidence Intervals In Survival Analysis,
2010
Universiti Malaya
Confidence Intervals In Survival Analysis, Tan Shay Kee
Student Works (2010-2019)
In obtaining confidence interval for the survivor function using Greenwood’s formula and in performing log-rank test for comparing the survivor functions of two groups of individuals, only the information given by the first two moments of the relevant statistics are used. Presently we show that by incorporating the information given by the third and fourth moments of the statistics, the performance of the confidence interval and statistical test can be improved. When the survivor function can be described by the Weibull distribution, the knowledge regarding the survivor function can be obtained through the estimation of the Weibull scale and shape …
A Markov Transition Model To Dementia With Death As A Competing Event,
2010
University of Kentucky
A Markov Transition Model To Dementia With Death As A Competing Event, Liou Xu
University of Kentucky Doctoral Dissertations
The research on multi-state Markov transition model is motivated by the nature of the longitudinal data from the Nun Study (Snowdon, 1997), and similar information on the BRAiNS cohort (Salazar, 2004). Our goal is to develop a flexible methodology for handling the categorical longitudinal responses and competing risks time-to-event that characterizes the features of the data for research on dementia. To do so, we treat the survival from death as a continuous variable rather than defining death as a competing absorbing state to dementia. We assume that within each subject the survival component and the Markov process are linked by …
Comparison Of Two Samples By A Nonparametric Likelihood-Ratio Test,
2010
University of Kentucky
Comparison Of Two Samples By A Nonparametric Likelihood-Ratio Test, William H. Barton
University of Kentucky Doctoral Dissertations
In this dissertation we present a novel computational method, as well as its software implementation, to compare two samples by a nonparametric likelihood-ratio test. The basis of the comparison is a mean-type hypothesis. The software is written in the R-language [4]. The two samples are assumed to be independent. Their distributions, which are assumed to be unknown, may be discrete or continuous. The samples may be uncensored, right-censored, left-censored, or doubly-censored. Two software programs are offered. The first program covers the case of a single mean-type hypothesis. The second program covers the case of multiple mean-type hypotheses. For the first …
Nonparametric Estimation Of Derivatives With Applications,
2010
University of Kentucky
Nonparametric Estimation Of Derivatives With Applications, Benjamin Hall
University of Kentucky Doctoral Dissertations
We review several nonparametric regression techniques and discuss their various strengths and weaknesses with an emphasis on derivative estimation and confidence band creation. We develop a generalized C(p) criterion for tuning parameter selection when interest lies in estimating one or more derivatives and the estimator is both linear in the observed responses and self-consistent. We propose a method for constructing simultaneous confidence bands for the mean response and one or more derivatives, where simultaneous now refers both to values of the covariate and to all derivatives under consideration. In addition we generalize the simultaneous confidence bands to account for heteroscedastic …
A Spline Kernel Based Smoothing Algorithm : A Comparison Of Methods With A Spatiotemporal Application To Global Climate Fluctuations,
2010
University at Albany, State University of New York
A Spline Kernel Based Smoothing Algorithm : A Comparison Of Methods With A Spatiotemporal Application To Global Climate Fluctuations, Derek Daniel Cyr
Legacy Theses & Dissertations (2009 - 2024)
In statistics, smoothing is a technique that attempts to capture the key patterns or trends in data while leaving out the noise that is obscuring them. Nonparametric techniques are well-suited for smoothing as they do not rely on assumptions that the data arise from a given probability distribution.
Effect Of Noise In Principal Component Analysis With An Application To Ozone Pollution,
2010
University at Albany, State University of New York
Effect Of Noise In Principal Component Analysis With An Application To Ozone Pollution, Katerina G. Tsakiri
Legacy Theses & Dissertations (2009 - 2024)
This thesis analyzes the effect of independent noise in principal components of k normally distributed random variables defined by a covariance matrix. We prove that the principal components as well as the canonical variate pairs determined from joint distribution of original sample affected by noise can be essentially different in comparison with those determined from the original sample. However when the differences between the eigenvalues of the original covariance matrix are sufficiently large compared to the level of the noise, the effect of noise in principal components and canonical variate pairs proved to be negligible. The theoretical results are supported …
Digraphs With Isomorphic Underlying And Domination Graphs: 4-Cycles And Pairs Of Paths,
2010
Marquette University
Digraphs With Isomorphic Underlying And Domination Graphs: 4-Cycles And Pairs Of Paths, 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), is created using the vertex set of D, V(D). There is an edge uv in dom(D) whenever (u, z) or (v, z) is in the arc set of D, A(D), for every other vertex z ε V(D). For only some digraphs D has the structure of dom(D) been characterized. Examples of this are tournaments and regular digraphs. The authors have characterizations for the structure of digraphs D for …
