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Articles 9301 - 9330 of 12860
Full-Text Articles in Statistics and Probability
Flipping The Winner Of A Poset Game, Adam O. Kalinich '12
Flipping The Winner Of A Poset Game, Adam O. Kalinich '12
Student Publications & Research
Partially-ordered set games, also called poset games, are a class of two-player combinatorial games. The playing field consists of a set of elements, some of which are greater than other elements. Two players take turns removing an element and all elements greater than it, and whoever takes the last element wins. Examples of poset games include Nim and Chomp. We investigate the complexity of computing which player of a poset game has a winning strategy. We give an inductive procedure that modifies poset games to change the nim-value which informally captures the winning strategies in the game. For a generic …
Assessing The Necessity Of Chimpanzee Experimentation, Andrew Knight
Assessing The Necessity Of Chimpanzee Experimentation, Andrew Knight
Experimentation Collection
No abstract provided.
A Guide To Defining And Implementing Protocols For The Welfare Assessment Of Laboratory Animals: Eleventh Report Of The Bvaawf/Frame/Rspca/Ufaw Joint Working Group On Refinement, P. Hawkins, D. B. Morton, O. Burman, N. Dennison, P. Honess, M. Jennings, S. Lane, V. Middleton, J. V. Roughan, S. Wells, K. Westwood
A Guide To Defining And Implementing Protocols For The Welfare Assessment Of Laboratory Animals: Eleventh Report Of The Bvaawf/Frame/Rspca/Ufaw Joint Working Group On Refinement, P. Hawkins, D. B. Morton, O. Burman, N. Dennison, P. Honess, M. Jennings, S. Lane, V. Middleton, J. V. Roughan, S. Wells, K. Westwood
Research Methodology and Laboratory Animals Collection
The refinement of husbandry and procedures to reduce animal suffering and improve welfare is an essential component of humane science. Successful refinement depends upon the ability to assess animal welfare effectively, and detect any signs of pain or distress as rapidly as possible, so that any suffering can be alleviated. This document provides practical guidance on setting up and operating effective protocols for the welfare assessment of animals used in research and testing. It sets out general principles for more objective observation of animals, recognizing and assessing indicators of pain or distress and tailoring these to individual projects. Systems for …
Testing The Mean For Business Data: Should One Use The Z-Test, T-Test, F-Test, The Chi-Square Test, Or The P-Value Method?, Jiajuan (John) Liang, William S. Pan
Testing The Mean For Business Data: Should One Use The Z-Test, T-Test, F-Test, The Chi-Square Test, Or The P-Value Method?, Jiajuan (John) Liang, William S. Pan
Marketing and Quantitative Analysis Faculty Publications
Purpose – The overall purpose of this research is to discuss the relationship among the tests for population mean that are taught in the Business Statistics course for business majors. Design/methodology/approach – The approach to this study is to describe the types of business data according to one-sample, two-sample, and multi-sample cases first and then combine tests for categorical data with tests for continuous data into a unified format on testing the mean of a population. Under this unified format, we summarize the methodology on the topic of testing the mean in business statistics course. Findings – One of the …
Self Learning Strategies For Experimental Design And Response Surface Optimization, Adel Alaeddini
Self Learning Strategies For Experimental Design And Response Surface Optimization, Adel Alaeddini
Wayne State University Dissertations
Most preset RSM designs offer ease of implementation and good performance over a wide range of process and design optimization applications. These designs often lack the ability to adapt the design based on the characteristics of application and experimental space so as to reduce the number of experiments necessary. Hence, they are not cost effective for applications where the cost of experimentation is high or when the experimentation resources are limited. In this dissertation, we present a number of self-learning strategies for optimization of different types of response surfaces for industrial experiments with noise, high experimentation cost, and requiring high …
Angiogenic Biomarkers For Risk Stratification In Women With Suspected Preeclampsia, Andreea Balan, Heather Young, Linda Ojo, Jennifer Keller, Sharon Maynard
Angiogenic Biomarkers For Risk Stratification In Women With Suspected Preeclampsia, Andreea Balan, Heather Young, Linda Ojo, Jennifer Keller, Sharon Maynard
Epidemiology Faculty Posters and Presentations
This poster presents the results of a single-center prospective cohort study of 315 pregnant women who presented to George Washington University Hospital Labor and Delivery service with a clinical suspicion of preeclampsia between February 2007 and November 2011. Informed consent was obtained. Baseline demographic information and medical history was collected on each patient including maternal age, ethnicity, body mass index, tobacco and other substance use, gestational age, medical problems and obstetric history. Serum samples were obtained from each enrolled subject within 24 hours of admission, and sFlt1, PlGF and sEng ELISA assays were performed in duplicate by a blinded laboratory …
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Model Selection In Validation Sampling Data: An Asymptotic Likelihood-Based Lasso Approach, Chenlei Leng, Denis H. Y. Leung
Research Collection School Of Economics
We propose an asymptotic likelihood-based LASSO approach for model selection in regression analysis when data are subject to validation sampling. The method makes use of an initial estimator of the regression coefficients and their asymptotic covariance matrix to form an asymptotic likelihood. This ``working'' objective function facilitates the formulation of the LASSO and the implementation of a fast algorithm. Our method circumvents the need to use a likelihood set-up that requires full distributional assumptions about the data. We show that the resulting estimator is consistent in model selection and that the method has lower prediction errors than a model that …
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Estimation And Forecasting Of Dynamic Conditional Covariance: A Semiparametric Multivariate Model, Xiangdong Long, Liangjun Su, Aman Ullah
Research Collection School Of Economics
We propose a semiparametric conditional covariance (SCC) estimator that combines the first-stage parametric conditional covariance (PCC) estimator with the second-stage nonparametric correction estimator in a multiplicative way. We prove the asymptotic normality of our SCC estimator, propose a nonparametric test for the correct specification of PCC models, and study its asymptotic properties. We evaluate the finite sample performance of our test and SCC estimator and compare the latter with that of PCC estimator, purely nonparametric estimator, and Hafner, Dijk, and Franses’s (2006) estimator in terms of mean squared error and Value-at-Risk losses via simulations and real data analyses.
Statistical Properties Of A Convoluted Beta-Weibull Distribution, Jianan Sun
Statistical Properties Of A Convoluted Beta-Weibull Distribution, Jianan Sun
Theses, Dissertations and Capstones
A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are the beta-normal (Eugene et.al. (2002)); beta-Gumbel (Nadarajah and Kotz (2004)); beta-exponential (Nadarajah and Kotz (2006)); beta-Weibull (Famoye et al. (2005)); beta-Rayleigh (Akinsete and Lowe (2008)); beta-Laplace (Kozubowski and Nadarajah (2008)); and beta-Pareto (Akinsete et al. (2008)), among a few others. Many useful statistical properties arising from these distributions and their applications to real life data have been discussed in the literature. One approach by which a new statistical distribution is generated is by the transformation of random variables having known …
Towards Transient Growth Analysis And Design In Iterative Learning Control, Douglas A. Bristow, John R. Singler
Towards Transient Growth Analysis And Design In Iterative Learning Control, Douglas A. Bristow, John R. Singler
Mechanical and Aerospace Engineering Faculty Research & Creative Works
In this article the problem of bounding transient growth in iterative learning control (ILC) is examined. While transient growth is not a desirable property, the alternative, robust monotonic convergence, leads to fundamental performance limitations. to circumvent these limitations, this article considers the possibility that some transient growth, if properly limited, is a viable and practical option. Towards this end, this article proposes tools for analysing worst-case transient growth in ILC. the proposed tools are based on pseudospectra analysis, which is extended to apply to ILC of uncertain systems. Two practical problems in norm-optimal ILC weighting parameter design are considered. Using …
Inflated Type I Error Rates When Using Aggregation Methods To Analyze Rare Variants In The 1000 Genomes Project Exon Sequencing Data In Unrelated Individuals: Summary Results From Group 7 At Genetic Analysis Workshop 17, Nathan L. Tintle, Hugues Aschard, Inchi Hu, Nora Nock, Haitian Wang, Elizabeth Pugh
Inflated Type I Error Rates When Using Aggregation Methods To Analyze Rare Variants In The 1000 Genomes Project Exon Sequencing Data In Unrelated Individuals: Summary Results From Group 7 At Genetic Analysis Workshop 17, Nathan L. Tintle, Hugues Aschard, Inchi Hu, Nora Nock, Haitian Wang, Elizabeth Pugh
Faculty Work Comprehensive List
As part of Genetic Analysis Workshop 17 (GAW17), our group considered the application of novel and standard approaches to the analysis of genotype-phenotype association in next-generation sequencing data. Our group identified a major issue in the analysis of the GAW17 next-generation sequencing data: type I error and false-positive report probability rates higher than those expected based on empirical type I error levels (as high as 90%). Two main causes emerged: population stratification and long-range correlation (gametic phase disequilibrium) between rare variants. Population stratification was expected because of the diverse sample. Correlation between rare variants was attributable to both random causes …
Identification Of Genetic Association Of Multiple Rare Variants Using Collapsing Methods, Yan V. Sun, Yun Ju Sung, Nathan L. Tintle, Andreas Ziegler
Identification Of Genetic Association Of Multiple Rare Variants Using Collapsing Methods, Yan V. Sun, Yun Ju Sung, Nathan L. Tintle, Andreas Ziegler
Faculty Work Comprehensive List
Next-generation sequencing technology allows investigation of both common and rare variants in humans. Exomes are sequenced on the population level or in families to further study the genetics of human diseases. Genetic Analysis Workshop 17 (GAW17) provided exomic data from the 1000 Genomes Project and simulated phenotypes. These data enabled evaluations of existing and newly developed statistical methods for rare variant sequence analysis for which standard statistical methods fail because of the rareness of the alleles. Various alternative approaches have been proposed that overcome the rareness problem by combining multiple rare variants within a gene. These approaches are termed collapsing …
Gis Will Affect The Political Landscape For The Next Decade And Beyond, Mark Salling
Gis Will Affect The Political Landscape For The Next Decade And Beyond, Mark Salling
All Maxine Goodman Levin School of Urban Affairs Publications
No abstract provided.
Epidemic Spread Of Influenza Viruses: The Impact Of Transient Populations On Disease Dynamics, Karen R. Ríos-Soto, Baojun Song, Carlos Castillo-Chavez
Epidemic Spread Of Influenza Viruses: The Impact Of Transient Populations On Disease Dynamics, Karen R. Ríos-Soto, Baojun Song, Carlos Castillo-Chavez
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
The recent H1N1 ("swine u") pandemic and recent H5N1 ("avian u") outbreaks have brought increased attention to the study of the role of animal populations as reservoirs for pathogens that could invade human populations. It is believed that pigs acquired u strains from birds and humans, acting as a mixing vessel in generating new influenza viruses. Assessing the role of animal reservoirs, particularly reservoirs involving highly mobile populations (like migratory birds), on disease dispersal and persistence is of interests to a wide range of researchers including public health experts and evolutionary biologists. This paper studies the interactions between transient and …
Decision Aid Models For Resource Sharing Strategies During Global Influenza Pandemics, Alfredo Santana Reynoso
Decision Aid Models For Resource Sharing Strategies During Global Influenza Pandemics, Alfredo Santana Reynoso
USF Tampa Graduate Theses and Dissertations
Pandemic influenza outbreaks have historically entailed significant societal and economic disruptions. Today, our quality of life is threatened by our inadequate preparedness for the imminent pandemic. The key challenges we are facing stem from a significant uncertainty in virus epidemiology, limited response resources, inadequate international collaboration, and the lack of appropriate science-based decision support tools. The existing literature falls short of comprehensive models for global pandemic spread and mitigation which incorporate the heterogeneity of the world regions and realistic travel networks. In addition, there exist virtually no studies which quantify the impact of resource sharing strategies among multiple countries. This …
Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar
Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar
Legacy Theses & Dissertations (2009 - 2024)
The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner.
Adjusted Empirical Likelihood Models With Estimating Equations For Accelerated Life Tests, Ni Wang, Jye-Chyi Lu, Di Chen, Paul H. Kvam
Adjusted Empirical Likelihood Models With Estimating Equations For Accelerated Life Tests, Ni Wang, Jye-Chyi Lu, Di Chen, Paul H. Kvam
Department of Math & Statistics Faculty Publications
This article proposes an adjusted empirical likelihood estimation (AMELE) method to model and analyze accelerated life testing data. This approach flexibly and rigorously incorporates distribution assumptions and regression structures by estimating equations within a semiparametric estimation framework. An efficient method is provided to compute the empirical likelihood estimates, and asymptotic properties are studied. Real-life examples and numerical studies demonstrate the advantage of the proposed methodology.
Adjusted Hazard Rate Estimator Based On A Known Censoring Probability, Ülkü Gürler, Paul H. Kvam
Adjusted Hazard Rate Estimator Based On A Known Censoring Probability, Ülkü Gürler, Paul H. Kvam
Department of Math & Statistics Faculty Publications
In most reliability studies involving censoring, one assumes that censoring probabilities are unknown. We derive a nonparametric estimator for the survival function when information regarding censoring frequency is available. The estimator is constructed by adjusting the Nelson–Aalen estimator to incorporate censoring information. Our results indicate significant improvements can be achieved if available information regarding censoring is used. We compare this model to the Koziol–Green model, which is also based on a form of proportional hazards for the lifetime and censoring distributions. Two examples of survival data help to illustrate the differences in the estimation techniques.
Multi-Cause Degradation Path Model: A Case Study On Rubidium Lamp Degradation, Sun Quan, Paul H. Kvam
Multi-Cause Degradation Path Model: A Case Study On Rubidium Lamp Degradation, Sun Quan, Paul H. Kvam
Department of Math & Statistics Faculty Publications
At the core of satellite rubidium standard clocks is the rubidium lamp, which is a critical piece of equipment in a satellite navigation system. There are many challenges in understanding and improving the reliability of the rubidium lamp, including the extensive lifetime requirement and the dearth of samples available for destructive life tests. Experimenters rely on degradation experiments to assess the lifetime distribution of highly reliable products that seem unlikely to fail under the normal stress conditions, because degradation data can provide extra information about product reliability. Based on recent research on the rubidium lamp, this article presents a multi‐cause …
On The First-Order Expressibility Of Lattice Properties To Unicoherence In Continua, Paul Bankston
On The First-Order Expressibility Of Lattice Properties To Unicoherence In Continua, Paul Bankston
Mathematics, Statistics and Computer Science Faculty Research and Publications
Many properties of compacta have “textbook” definitions which are phrased in lattice-theoretic terms that, ostensibly, apply only to the full closed-set lattice of a space. We provide a simple criterion for identifying such definitions that may be paraphrased in terms that apply to all lattice bases of the space, thereby making model-theoretic tools available to study the defined properties. In this note we are primarily interested in properties of continua related to unicoherence; i.e., properties that speak to the existence of “holes” in a continuum and in certain of its subcontinua.
Detecting Temporal Patterns Using Reconstructed Phase Space And Support Vector Machine In The Dynamic Data System, Wenjing Zhang, Xin Feng
Detecting Temporal Patterns Using Reconstructed Phase Space And Support Vector Machine In The Dynamic Data System, Wenjing Zhang, Xin Feng
Mathematics, Statistics and Computer Science Faculty Research and Publications
In this paper we present a method for detecting dynamic temporal patterns that are characteristic and predictive of significant events in a dynamic data system. We employ the Gaussian Mixture Model (GMM) to cluster the data sequence into three categories of signals, e.g. normal, patterns and events. The data sequence is then embedded into a Reconstructed Phase Space (RPS) which is topologically equivalent to the dynamics of the original system. We apply a hybrid method using Support Vector Machines (SVM) and Maximum a Posterior (MAP) to classify temporal pattern signals based on the event function. We performed two experimental applications …
Impact Of Curriculum Reform: Evidence Of Change In Classroom Instruction In The United States, John Moyer, Jinfa Cai, Ning Wang, Bikai Nie
Impact Of Curriculum Reform: Evidence Of Change In Classroom Instruction In The United States, John Moyer, Jinfa Cai, Ning Wang, Bikai Nie
Mathematics, Statistics and Computer Science Faculty Research and Publications
The purpose of the study reported in this article is to examine the impact of curriculum on instruction. Over a three-year period, we observed 579 algebra-related lessons in grades 6–8. Approximately half the lessons were taught in schools that had adopted a Standards-based mathematics curriculum called the Connected Mathematics Program (CMP), and the remainder of the lessons were taught in schools that used more traditional curricula (non-CMP). We found many significant differences between the CMP and non-CMP lessons. The CMP lessons, emphasized the conceptual aspects of instruction to a greater extent than the non-CMP lessons and the non-CMP lessons …
On The Distributions Of Certain Spacings, Gholamhossein Hamedani, Hans Volkmer
On The Distributions Of Certain Spacings, Gholamhossein Hamedani, Hans Volkmer
Mathematics, Statistics and Computer Science Faculty Research and Publications
A characterization of the uniform distribution based on distributions of spacings is presented which extends the existing result in this direction. Also, a result on the distribution of spacings for distributions close to the uniform one is discussed.
Drag Reduction Of A Modern Straight Truck, Drew Landman, Matthew Cragun, Mike Mccormick, Richard Wood
Drag Reduction Of A Modern Straight Truck, Drew Landman, Matthew Cragun, Mike Mccormick, Richard Wood
Mechanical & Aerospace Engineering Faculty Publications
A wind tunnel test program was conducted at the Langley Full Scale Tunnel (LFST) to evaluate the performance of five passive drag reduction configurations on a modern straight truck at full scale. Configurations were tested in a build-up fashion with results representing a cumulative effect. Tested configurations include a front valance, a front box fairing, a boat-tail, an ideal side-skirt, and a practical side-skirt. Configurations were evaluated over a nominal 9 degree yaw sweep to establish wind averaged drag coefficients using SAE J1252. Genuine replicate yaw sweeps were used in an uncertainty analysis. Results show up to 28% improvement in …
Studies In Sampling Techniques And Time Series Analysis, Florentin Smarandache, Rajesh Singh
Studies In Sampling Techniques And Time Series Analysis, Florentin Smarandache, Rajesh Singh
Branch Mathematics and Statistics Faculty and Staff Publications
This book has been designed for students and researchers who are working in the field of time series analysis and estimation in finite population. There are papers by Rajesh Singh, Florentin Smarandache, Shweta Maurya, Ashish K. Singh, Manoj Kr. Chaudhary, V. K. Singh, Mukesh Kumar and Sachin Malik. First chapter deals with the problem of time series analysis and the rest of four chapters deal with the problems of estimation in finite population. The book is divided in five chapters as follows: Chapter 1. Water pollution is a major global problem. In this chapter, time series analysis is carried out …
Uniform And Partially Uniform Redistribution Rules, Florentin Smarandache, Jean Dezert
Uniform And Partially Uniform Redistribution Rules, Florentin Smarandache, Jean Dezert
Branch Mathematics and Statistics Faculty and Staff Publications
This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.
Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh
Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh
Branch Mathematics and Statistics Faculty and Staff Publications
This article addresses the problem of estimating the population mean using auxiliary information in the presence of measurement errors.
Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty
Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty
Mathematics & Statistics Faculty Publications
There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our …
Essays On Hedge Fund Replication: Methodological Assessment And Development Of The Factor Approach, Nonlinear Modeling And Policy Perspectives, Guillaume Weisang
Essays On Hedge Fund Replication: Methodological Assessment And Development Of The Factor Approach, Nonlinear Modeling And Policy Perspectives, Guillaume Weisang
2011
This dissertation is concerned with hedge fund replication, a subject of a practical and theoretical importance, both from an investment and a risk management point of view. One of our goals is to extend known methodologies in order to enhance our understanding of an industry that is known for its secrecy and its lack of transparency. A second goal is to contribute to the quantitative finance literature with improved techniques for hedge fund replication. Hedge fund replication (HFR) is approached from the methodological as well as from practical and regulatory perspectives. The first two chapters provide the motivation and the …
Parametric Estimation In Competing Risks And Multi-State Models, Yushun Lin
Parametric Estimation In Competing Risks And Multi-State Models, Yushun Lin
Theses and Dissertations--Statistics
The typical research of Alzheimer's disease includes a series of cognitive states. Multi-state models are often used to describe the history of disease evolvement. Competing risks models are a sub-category of multi-state models with one starting state and several absorbing states.
Analyses for competing risks data in medical papers frequently assume independent risks and evaluate covariate effects on these events by modeling distinct proportional hazards regression models for each event. Jeong and Fine (2007) proposed a parametric proportional sub-distribution hazard (SH) model for cumulative incidence functions (CIF) without assumptions about the dependence among the risks. We modified their model to …