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Articles 211 - 240 of 546
Full-Text Articles in Statistics and Probability
Genetic Analysis Workshop 18: Methods And Strategies For Analyzing Human Sequence And Phenotype Data In Members Of Extended Pedigrees, Heike Bickeboller, Julia N. Bailey, Joseph Beyene, Rita M. Cantor, Heather J. Cordell, Robert C. Culverhouse, Corinne D. Engelman, David W. Fardo, Saurabh Ghosh, Inke R. Konig, Justo Lorenzo Bermejo, Phillip E. Melton, Stephanie A. Santorico, Glen A. Satten, Lei Sun, Nathan L. Tintle, Andreas Ziegler, Jean W. Maccluer, Laura Almasy
Genetic Analysis Workshop 18: Methods And Strategies For Analyzing Human Sequence And Phenotype Data In Members Of Extended Pedigrees, Heike Bickeboller, Julia N. Bailey, Joseph Beyene, Rita M. Cantor, Heather J. Cordell, Robert C. Culverhouse, Corinne D. Engelman, David W. Fardo, Saurabh Ghosh, Inke R. Konig, Justo Lorenzo Bermejo, Phillip E. Melton, Stephanie A. Santorico, Glen A. Satten, Lei Sun, Nathan L. Tintle, Andreas Ziegler, Jean W. Maccluer, Laura Almasy
Faculty Work Comprehensive List
Genetic Analysis Workshop 18 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence data from a pedigree-based sample. In this article we present an overview of the data sets and the contributions that analyzed these data. The family data, donated by the Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Ethnic Samples Consortium, included sequence-level genotypes based on sequencing and imputation, genome-wide association genotypes from prior genotyping arrays, and phenotypes from longitudinal assessments. The contributions from individual research groups were extensively discussed before, during, and after the workshop in theme-based discussion groups before being submitted …
A 2-Step Penalized Regression Method For Family-Based Next-Generation Sequencing Association Studies, Xiuhua Ding, Shaoyong Su, Kannabiran Nandakumar, Xiaoling Wang, David W. Fardo
A 2-Step Penalized Regression Method For Family-Based Next-Generation Sequencing Association Studies, Xiuhua Ding, Shaoyong Su, Kannabiran Nandakumar, Xiaoling Wang, David W. Fardo
Biostatistics Faculty Publications
Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correlation from familial relatedness and then uses the resulting phenotypic residuals in a penalized regression framework to test for associations with variants within genetic units. The operating characteristics of this approach are detailed using simulation data based on a large, multigenerational cohort.
Modeling Of Multivariate Longitudinal Phenotypes In Family Genetic Studies With Bayesian Multiplicity Adjustment, Lili Ding, Brad G. Kurowski, Hua He, Eileen S. Alexander, Tesfaye B. Mersha, David Fardo, Xue Zhang, Valentina V. Pilipenko, Leah Kottyan, Lisa J. Martin
Modeling Of Multivariate Longitudinal Phenotypes In Family Genetic Studies With Bayesian Multiplicity Adjustment, Lili Ding, Brad G. Kurowski, Hua He, Eileen S. Alexander, Tesfaye B. Mersha, David Fardo, Xue Zhang, Valentina V. Pilipenko, Leah Kottyan, Lisa J. Martin
Biostatistics Faculty Publications
Genetic studies often collect data on multiple traits. Most genetic association analyses, however, consider traits separately and ignore potential correlation among traits, partially because of difficulties in statistical modeling of multivariate outcomes. When multiple traits are measured in a pedigree longitudinally, additional challenges arise because in addition to correlation between traits, a trait is often correlated with its own measures over time and with measurements of other family members. We developed a Bayesian model for analysis of bivariate quantitative traits measured longitudinally in family genetic studies. For a given trait, family-specific and subject-specific random effects account for correlation among family …
Application Of Family-Based Tests Of Association For Rare Variants To Pathways, Brian Greco, Alexander Luedtke, Allison Hainline, Carolina Alvarez, Andrew Beck, Nathan L. Tintle
Application Of Family-Based Tests Of Association For Rare Variants To Pathways, Brian Greco, Alexander Luedtke, Allison Hainline, Carolina Alvarez, Andrew Beck, Nathan L. Tintle
Faculty Work Comprehensive List
Pathway analysis approaches for sequence data typically either operate in a single stage (all variants within all genes in the pathway are combined into a single, very large set of variants that can then be analyzed using standard “gene-based” test statistics) or in 2-stages (gene-based p values are computed for all genes in the pathway, and then the gene-based p values are combined into a single pathway p value). To date, little consideration has been given to the performance of gene-based tests (typically designed for a smaller number of single-nucleotide variants [SNVs]) when the number of SNVs in the gene …
Interadapt -- An Interactive Tool For Designing And Evaluating Randomized Trials With Adaptive Enrollment Criteria, Aaron Joel Fisher, Harris Jaffee, Michael Rosenblum
Interadapt -- An Interactive Tool For Designing And Evaluating Randomized Trials With Adaptive Enrollment Criteria, Aaron Joel Fisher, Harris Jaffee, Michael Rosenblum
Johns Hopkins University, Dept. of Biostatistics Working Papers
The interAdapt R package is designed to be used by statisticians and clinical investigators to plan randomized trials. It can be used to determine if certain adaptive designs offer tangible benefits compared to standard designs, in the context of investigators’ specific trial goals and constraints. Specifically, interAdapt compares the performance of trial designs with adaptive enrollment criteria versus standard (non-adaptive) group sequential trial designs. Performance is compared in terms of power, expected trial duration, and expected sample size. Users can either work directly in the R console, or with a user-friendly shiny application that requires no programming experience. Several added …
Vitamin D Status And Demographic And Lifestyle Determinants Among Adults In The United States (Nhanes 2001-2006), Yan Cao, Katie L. Callahan, Sreenivas P. Veeranki, Yang Chen, Ying Liu, Shimin Zheng
Vitamin D Status And Demographic And Lifestyle Determinants Among Adults In The United States (Nhanes 2001-2006), Yan Cao, Katie L. Callahan, Sreenivas P. Veeranki, Yang Chen, Ying Liu, Shimin Zheng
ETSU Faculty Works
This study looked at risk factors associated with vitamin D levels in the body among a representative sample of adults in the U.S., NHANES III (2001-2006) data were used to assess the relationship between several demographic and health risk factors and vitamin D levels in the body. The Baseline-Category Logit Model was used to test the association between vitamin D level and the potential risk factors age, education, ethnicity, poverty status, physical activity, smoking, alcohol, obesity, diabetes and total cholesterol with both genders. Vitamin D insufficiency and deficiency were significantly associated with age, race, education, physical activity, obesity, diabetes and …
The Impact Of Student Performance On Large-Scale Assessments: A View Of Long-Term Health, Career, And Societal Outcomes, Roman Usatin
The Impact Of Student Performance On Large-Scale Assessments: A View Of Long-Term Health, Career, And Societal Outcomes, Roman Usatin
Seton Hall University Dissertations and Theses (ETDs)
This study examined the predictive power of student growth for large-scale assessments on meaningful life outcomes, focusing on the three categories of health, career, and societal involvement. Analysis was conducted using the NELS:88/00 dataset–a longitudinal study that followed a nationally-representative sample of over 12,000 eighth grade students from 1988 to 2000, until the students were 26 years old and entered into the work force. The large-scale assessment variables included math and reading performance in the 1988 cognitive batteries administered by NELS. To gauge growth levels, I generated Student Growth Percentiles (SGP) from tests administered by NELS from 1988 to 1992. …
Methods For Exploring Treatment Effect Heterogeneity In Subgroup Analysis: An Application To Global Clinical Trials, I. Manjula Schou, Ian C. Marschner
Methods For Exploring Treatment Effect Heterogeneity In Subgroup Analysis: An Application To Global Clinical Trials, I. Manjula Schou, Ian C. Marschner
COBRA Preprint Series
Multi-country randomised clinical trials (MRCTs) are common in the medical literature and their interpretation has been the subject of extensive recent discussion. In many MRCTs, an evaluation of treatment effect homogeneity across countries or regions is conducted. Subgroup analysis principles require a significant test of interaction in order to claim heterogeneity of treatment effect across subgroups, such as countries in a MRCT. As clinical trials are typically underpowered for tests of interaction, overly optimistic expectations of treatment effect homogeneity can lead researchers, regulators and other stakeholders to over-interpret apparent differences between subgroups even when heterogeneity tests are insignificant. In this …
How Sexism Makes The Man: Examining The Relationship Between Masculinity, Ambivalent Sexism, And Gender Stereotyping, Mariah L. Wilkerson
How Sexism Makes The Man: Examining The Relationship Between Masculinity, Ambivalent Sexism, And Gender Stereotyping, Mariah L. Wilkerson
Lawrence University Honors Projects
Masculinity is a precarious social status, meaning it can be lost through social and gender transgressions (Bosson & Vandello, 2011). Men often act in stereotypically masculine ways to reassert their masculinity and restore their social status after it has been threatened. The current study also examines masculinity in a new way, as a collective gender identity (e.g., Tajfel, 1982). I hypothesized that threatened men and men who identify as more masculine will display masculinity through more polarized attitudes towards traditional and nontraditional groups of men and women, endorsing traditional gender stereotypes, and intensified ambivalently sexist attitudes. Two empirical studies tested …
Trend Analysis And Modeling Of Health And Environmental Data: Joinpoint And Functional Approach, Ram C. Kafle
Trend Analysis And Modeling Of Health And Environmental Data: Joinpoint And Functional Approach, Ram C. Kafle
USF Tampa Graduate Theses and Dissertations
The present study is divided into two parts: the first is on developing the statistical analysis and modeling of mortality (or incidence) trends using Bayesian joinpoint regression and the second is on fitting differential equations from time series data to derive the rate of change of carbon dioxide in the atmosphere.
Joinpoint regression model identifies significant changes in the trends of the incidence, mortality, and survival of a specific disease in a given population. Bayesian approach of joinpoint regression is widely used in modeling statistical data to identify the points in the trend where the significant changes occur. The purpose …
Pgs: A Tool For Association Study Of High-Dimensional Microrna Expression Data With Repeated Measures, Yinan Zheng, Zhe Fei, Wei Zhang, Justin Starren, Lei Liu, Andrea Baccarelli, Yi Li, Lifang Hou
Pgs: A Tool For Association Study Of High-Dimensional Microrna Expression Data With Repeated Measures, Yinan Zheng, Zhe Fei, Wei Zhang, Justin Starren, Lei Liu, Andrea Baccarelli, Yi Li, Lifang Hou
The University of Michigan Department of Biostatistics Working Paper Series
Motivation: MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Due to interested in the dynamic nature of the miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNAs expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time. However, the commonly used site-by-site multiple testing may impair the value of repeated or multiple measures data by ignoring the inherent dependent structure, which lead to problems including underpowered results after multiple comparison …
Targeted Maximum Likelihood Estimation Using Exponential Families, Iván Díaz, Michael Rosenblum
Targeted Maximum Likelihood Estimation Using Exponential Families, Iván Díaz, Michael Rosenblum
Johns Hopkins University, Dept. of Biostatistics Working Papers
Targeted maximum likelihood estimation (TMLE) is a general method for estimating parameters in semiparametric and nonparametric models. Each iteration of TMLE involves fitting a parametric submodel that targets the parameter of interest. We investigate the use of exponential families to define the parametric submodel. This implementation of TMLE gives a general approach for estimating any smooth parameter in the nonparametric model. A computational advantage of this approach is that each iteration of TMLE involves estimation of a parameter in an exponential family, which is a convex optimization problem for which software implementing reliable and computationally efficient methods exists. We illustrate …
Flint International Statistics Conference Agenda, Kettering University
Flint International Statistics Conference Agenda, Kettering University
Flint: One City, 100 Years of Variability
Conference Agenda—Keynote Speakers, Invited & Contributed Talks, Posters, Field Trips
- Tuesday, June 24
- Wednesday, June 25
- Thursday, June 26
- Friday, June 27
- Saturday, June 28
Select Sessions:
- Elart von Collani “Statistics as a general tool for all sciences.”
- Francesca Greselin “Measuring inequality at the time of the Great Divergence.”
- Ernest Fokoue “Recent Applications of Statistical Data Mining for Big Data Predictive Analysis.”
- Vladimir Kaishev “Probability and statistics in actuarial applications.”
- Galia Novikova “Data Mining for Software Development Quality Management.”
- Leda Minkova “Stochastic Models and Statistical Applications.”
- Krzysztof Podgorski “Non-Gaussian stochastic models: theory and applications.”
- Kristina Sendova “Risk measures, probability measures …
Extreme Self-Adjoint Extensions Of A Semibounded Q-Difference Operator, Miron B. Bekker, Martin Bohner, Hristo Voulov
Extreme Self-Adjoint Extensions Of A Semibounded Q-Difference Operator, Miron B. Bekker, Martin Bohner, Hristo Voulov
Mathematics and Statistics Faculty Research & Creative Works
For a certain q-difference operator introduced and studied in a series of articles by the same authors, we investigate its extreme self-adjoint extensions, i.e., the so-called Friedrichs and Kreǐn extensions. We show that for the interval of parameters under consideration, the Friedrichs extension and the Kreǐn extension are distinct and give values of the parameter in the von Neumann formulas that correspond to those extensions and describe their resolvent operators. A crucial role in our investigation plays the fact that both the Friedrichs and the Kreǐn extensions are scale invariant. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Simulating Influenza Transmission With Network Data, Henry V. Bongiovi
Simulating Influenza Transmission With Network Data, Henry V. Bongiovi
Statistics
Simulating Influenza Transmission with Real Network Data
Henry Bongiovi BS Statistics, California Polytechnic State University, San Luis Obispo
Keywords: Network Data, Simulation, Education, Influenza, Epidemic
Disease has been humanities arch rival since the dawn of our existence. As such, we have been trying our best to understand its spread and proliferation. One of the most common diseases, Influenza, is also one of the most complex. To understand the complexities of its spread would greatly improve our ability to combat it and other diseases like it. Using R in conjunction with the package statnet, I have created a simulation of …
Gwas Identifies An Nat2 Acetylator Status Tag Single Nucleotide Polymorphism To Be A Major Locus For Skin Fluorescence, Karen M. Eny, Helen L. Lutgers, John Maynard, Barbara E.K. Klein, Kristine E. Lee, Patricia A. Cleary, +20 Additional Authors
Gwas Identifies An Nat2 Acetylator Status Tag Single Nucleotide Polymorphism To Be A Major Locus For Skin Fluorescence, Karen M. Eny, Helen L. Lutgers, John Maynard, Barbara E.K. Klein, Kristine E. Lee, Patricia A. Cleary, +20 Additional Authors
Epidemiology Faculty Publications
Aims/hypothesis
Skin fluorescence (SF) is a non-invasive marker of AGEs and is associated with the long-term complications of diabetes. SF increases with age and is also greater among individuals with diabetes. A familial correlation of SF suggests that genetics may play a role. We therefore performed parallel genome-wide association studies of SF in two cohorts.
Methods
Cohort 1 included 1,082 participants, 35–67 years of age with type 1 diabetes. Cohort 2 included 8,721 participants without diabetes, aged 18–90 years.
Results
rs1495741 was significantly associated with SF in Cohort 1 (p < 6 × 10−10), which is known to tag theNAT2 acetylator phenotype. The fast acetylator genotype was associated …
Abcc9 Gene Polymorphism Is Associated With Hippocampal Sclerosis Of Aging Pathology, Peter T. Nelson, Steven Estus, Erin L. Abner, Ishita Parikh, Manasi Malik, Janna H. Neltner, Eseosa Ighodaro, Wang-Xia Wang, Bernard R. Wilfred, Li-San Wang, Walter A. Kukull, Kannabiran Nandakumar, Mark L. Farman, Wayne W. Poon, Maria M. Corrada, Claudia H. Kawas, David H. Cribbs, David A. Bennett, Julie A. Schneider, Eric B. Larson, Paul K. Crane, Otto Valladares, Frederick A. Schmitt, Richard J. Kryscio, Gregory A. Jicha, Charles D. Smith, Stephen W. Scheff, Joshua A. Sonnen, Jonathan L. Haines, Margaret A. Pericak-Vance, Richard Mayeux, Lindsay A. Farrer, Linda J. Van Eldik, Craig Horbinski, Robert C. Green, Marla Gearing, Leonard W. Poon, Patricia L. Kramer, Randall L. Woltjer, Thomas J. Montine, Amanda B. Partch, Alexander J. Rajic, Katierose Richmire, Sarah E. Monsell, Gerard D. Schellenberg, David W. Fardo
Abcc9 Gene Polymorphism Is Associated With Hippocampal Sclerosis Of Aging Pathology, Peter T. Nelson, Steven Estus, Erin L. Abner, Ishita Parikh, Manasi Malik, Janna H. Neltner, Eseosa Ighodaro, Wang-Xia Wang, Bernard R. Wilfred, Li-San Wang, Walter A. Kukull, Kannabiran Nandakumar, Mark L. Farman, Wayne W. Poon, Maria M. Corrada, Claudia H. Kawas, David H. Cribbs, David A. Bennett, Julie A. Schneider, Eric B. Larson, Paul K. Crane, Otto Valladares, Frederick A. Schmitt, Richard J. Kryscio, Gregory A. Jicha, Charles D. Smith, Stephen W. Scheff, Joshua A. Sonnen, Jonathan L. Haines, Margaret A. Pericak-Vance, Richard Mayeux, Lindsay A. Farrer, Linda J. Van Eldik, Craig Horbinski, Robert C. Green, Marla Gearing, Leonard W. Poon, Patricia L. Kramer, Randall L. Woltjer, Thomas J. Montine, Amanda B. Partch, Alexander J. Rajic, Katierose Richmire, Sarah E. Monsell, Gerard D. Schellenberg, David W. Fardo
Pathology and Laboratory Medicine Faculty Publications
Hippocampal sclerosis of aging (HS-Aging) is a high-morbidity brain disease in the elderly but risk factors are largely unknown. We report the first genome-wide association study (GWAS) with HS-Aging pathology as an endophenotype. In collaboration with the Alzheimer's Disease Genetics Consortium, data were analyzed from large autopsy cohorts: (#1) National Alzheimer's Coordinating Center (NACC); (#2) Rush University Religious Orders Study and Memory and Aging Project; (#3) Group Health Research Institute Adult Changes in Thought study; (#4) University of California at Irvine 90+ Study; and (#5) University of Kentucky Alzheimer's Disease Center. Altogether, 363 HS-Aging cases and 2,303 controls, all pathologically …
Rapid Door-To-Balloon Time (≤ 30 Minutes) In The Treatment Of Acute St-Elevation Myocardial Infarction (Stemi) Is Associated With Reduced Length Of Hospital Stay And Improved Clinical Outcomes, Yassir Nawaz Md, Ataul Qureshi Md, Navin K. Subrayappa Md, Orlando E. Rivera Rn, Bruce Feldman Do, Nainesh C. Patel Md
Rapid Door-To-Balloon Time (≤ 30 Minutes) In The Treatment Of Acute St-Elevation Myocardial Infarction (Stemi) Is Associated With Reduced Length Of Hospital Stay And Improved Clinical Outcomes, Yassir Nawaz Md, Ataul Qureshi Md, Navin K. Subrayappa Md, Orlando E. Rivera Rn, Bruce Feldman Do, Nainesh C. Patel Md
Department of Medicine
No abstract provided.
Understanding Non-Emergent Pediatric Ed Visits: Using Hospital And Family Centric Data To Inform System Redesign, Deborah Swavely Dnp, Rn, Kathy Baker Mph, Rn, Krista L. Bilger Bsn, Rn, David Zimmerman Mph, Andrew Martin Msn, Rn
Understanding Non-Emergent Pediatric Ed Visits: Using Hospital And Family Centric Data To Inform System Redesign, Deborah Swavely Dnp, Rn, Kathy Baker Mph, Rn, Krista L. Bilger Bsn, Rn, David Zimmerman Mph, Andrew Martin Msn, Rn
Department of Community Health and Health Studies
No abstract provided.
The Inferred Cardiogenic Gene Regulatory Network In The Mammalian Heart, Jason Bazil, Karl D. Stamm, Xing Li, Raghuram Thiagarajan, Timonthy J. Nelson, Aoy Tomita-Mitchell, Daniel A. Beard
The Inferred Cardiogenic Gene Regulatory Network In The Mammalian Heart, Jason Bazil, Karl D. Stamm, Xing Li, Raghuram Thiagarajan, Timonthy J. Nelson, Aoy Tomita-Mitchell, Daniel A. Beard
Mathematics, Statistics and Computer Science Faculty Research and Publications
Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from the developing mouse heart. Approximately 200 genes of interest were input into the algorithm to generate putative network topologies that are capable of explaining the experimental data via model simulation. To cull specious network interactions, thousands of putative networks are merged and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene …
Measurement Error In The Afqt In The Nlsy79, Lynne Steuerle Schofield
Measurement Error In The Afqt In The Nlsy79, Lynne Steuerle Schofield
Mathematics & Statistics Faculty Works
Many promising efforts in the social sciences aim to measure future outcomes (such as wages or health outcomes) given some base level of human capital or ability. They typically fail to recognize the proxies for human capital are all measured with error, creating bias in regression analysis. Here I show how item level data offers the opportunity to improve a broad range of economic, social and psychometric studies, an opportunity now enhanced significantly by the new release of item response level data for the Armed Forces Qualifying Test in the 1979 National Longitudinal Survey of Youth. (c) 2014 Elsevier B.V. …
Self-Reported Head Injury And Risk Of Late-Life Impairment And Ad Pathology In An Ad Center Cohort, Erin L. Abner, Peter T. Nelson, Frederick A. Schmitt, Steven R. Browning, David W. Fardo, Lijie Wan, Gregory A. Jicha, Gregory E. Cooper, Charles D. Smith, Allison M. Caban-Holt, Linda J. Van Eldik, Richard J. Kryscio
Self-Reported Head Injury And Risk Of Late-Life Impairment And Ad Pathology In An Ad Center Cohort, Erin L. Abner, Peter T. Nelson, Frederick A. Schmitt, Steven R. Browning, David W. Fardo, Lijie Wan, Gregory A. Jicha, Gregory E. Cooper, Charles D. Smith, Allison M. Caban-Holt, Linda J. Van Eldik, Richard J. Kryscio
Sanders-Brown Center on Aging Faculty Publications
Aims: To evaluate the relationship between self-reported head injury and cognitive impairment, dementia, mortality, and Alzheimer's disease (AD)-type pathological changes. Methods: Clinical and neuropathological data from participants enrolled in a longitudinal study of aging and cognition (n = 649) were analyzed to assess the chronic effects of self-reported head injury. Results: The effect of self-reported head injury on the clinical state depended on the age at assessment: for a 1-year increase in age, the OR for the transition to clinical mild cognitive impairment (MCI) at the next visit for participants with a history of head injury was 1.21 and 1.34 …
A New Adjustment Of Laplace Transform For Fractional Bloch Equation In Nmr Flow, Sunil Kumar, Devendra Kumar, U. S. Mahabaleshwar
A New Adjustment Of Laplace Transform For Fractional Bloch Equation In Nmr Flow, Sunil Kumar, Devendra Kumar, U. S. Mahabaleshwar
Applications and Applied Mathematics: An International Journal (AAM)
This work purpose suggest a new analytical technique called the fractional homotopy analysis transform method (FHATM) for solving time fractional Bloch NMR (nuclear magnetic resonance) flow equations, which are a set of macroscopic equations that are used for modeling nuclear magnetization as a function of time. The true beauty of this article is the coupling of the homotopy analysis method and the Laplace transform method for systems of fractional differential equations. The solutions obtained by the proposed method indicate that the approach is easy to implement and computationally very attractive.
Beta Burr Xii Or Five Parameter Beta Lomax Distribution: Remarks And Characterizations, Z. Javanshiri, Mehdi Maadooliat
Beta Burr Xii Or Five Parameter Beta Lomax Distribution: Remarks And Characterizations, Z. Javanshiri, Mehdi Maadooliat
Mathematics, Statistics and Computer Science Faculty Research and Publications
The distributions taken up in two recently published papers are compared and certain characterizations of them are presented. These characterizations are based on: (i) a simple relationship between two truncated moments; (ii) truncated moments of certain functions of the nth order statistic; (iii) truncated moments of certain functions of the random variable.
Regularized Multivariate Regression Models With Skew-T Error Distributions, Lianfu Chen, Mohsen Pourahmadi, Mehdi Maadooliat
Regularized Multivariate Regression Models With Skew-T Error Distributions, Lianfu Chen, Mohsen Pourahmadi, Mehdi Maadooliat
Mathematics, Statistics and Computer Science Faculty Research and Publications
We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both the regression coefficient and inverse scale matrices simultaneously. The sparsity is introduced through penalizing the negative log-likelihood by adding L1-penalties on the entries of the two matrices. Taking advantage of the hierarchical representation of skew-t distributions, and using the expectation conditional maximization (ECM) algorithm, we reduce the problem to penalized normal likelihood and develop a procedure to minimize the ensuing objective function. Using a …
A Characterization Of Skew Normal Distribution By Truncated Moment, M. Shakil, M. M. Ahsanullah, B. M. Golam Kibria
A Characterization Of Skew Normal Distribution By Truncated Moment, M. Shakil, M. M. Ahsanullah, B. M. Golam Kibria
Applications and Applied Mathematics: An International Journal (AAM)
A probability distribution can be characterized through various methods. This paper discusses a new characterization of skew normal distribution by truncated moment. It is hoped that the findings of the paper will be useful for researchers in different fields of applied sciences
Stochastic Modeling Of A Concrete Mixture Plant With Preventive Maintenance, Ashish Kumar, Monika Saini, S. C. Malik
Stochastic Modeling Of A Concrete Mixture Plant With Preventive Maintenance, Ashish Kumar, Monika Saini, S. C. Malik
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, a stochastic model for concrete mixture plant with Preventive Maintenance (PM) is analyzed in detail by using a supplementary variable technique. In a concrete mixture plant eight subsystems are arranged in a series. The system goes under PM after a maximum operation time and work as new after PM. The time to failure of each subsystem follows a negative exponential distribution while PM and repair time distributions are taken as arbitrary. A sufficient repair facility is provided to the system for conducting PM and repair of the system. Repair, maintenance and switch devices are perfect. All random …
Acceptance Sampling Plans For Percentiles Based On The Exponentiated Half Logistic Distribution, G. S. Rao, Ch. R. Naidu
Acceptance Sampling Plans For Percentiles Based On The Exponentiated Half Logistic Distribution, G. S. Rao, Ch. R. Naidu
Applications and Applied Mathematics: An International Journal (AAM)
In this article, acceptance sampling plans are developed for the exponentiated half logistic distribution percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer’s risk. The operating characteristic values (and curves) of the sampling plans as well as the producer’s risk are presented. Two examples with real data sets are also given as illustration.
A Ranking Method Based On Common Weights And Benchmark Point, Ali Payan, Abbas A. Noora, Farhad H. Lotfi
A Ranking Method Based On Common Weights And Benchmark Point, Ali Payan, Abbas A. Noora, Farhad H. Lotfi
Applications and Applied Mathematics: An International Journal (AAM)
The highest efficiency score 1 (100% efficiency) is regarded as a common benchmark for Decision Making Units (DMUs). This brings about the existence of more than one DMU with the highest score. Such a case normally occurs in all Data Envelopment Analysis (DEA) models and also in all the Common Set of Weights (CSWs) methods and it may lead to the lack of thorough ranking of DMUs. And ideal DMU based on its specific structure is a unit that no unit would do better than. Therefore, it can be utilized as a benchmark for other units. We are going to …
Counting Independent Sets Of A Fixed Size In Graphs With Given Minimum Degree, John Engbers, David Galvin
Counting Independent Sets Of A Fixed Size In Graphs With Given Minimum Degree, John Engbers, David Galvin
Mathematics, Statistics and Computer Science Faculty Research and Publications
Galvin showed that for all fixed δ and sufficiently large n, the n-vertex graph with minimum degree δ that admits the most independent sets is the complete bipartite graph . He conjectured that except perhaps for some small values of t, the same graph yields the maximum count of independent sets of size t for each possible t. Evidence for this conjecture was recently provided by Alexander, Cutler, and Mink, who showed that for all triples with , no n-vertex bipartite graph with minimum degree δ admits more independent sets of size t than . …