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Articles 9721 - 9750 of 12911
Full-Text Articles in Statistics and Probability
Desiderata For A Predictive Theory Of Statistics, Bertrand Clarke
Desiderata For A Predictive Theory Of Statistics, Bertrand Clarke
Department of Statistics: Faculty Publications
In many contexts the predictive validation of models or their associated prediction strategies is of greater importance than model identification which may be practically impossible. This is particularly so in fields involving complex or high dimensional data where model selection, or more generally predictor selection is the main focus of effort. This paper suggests a unified treatment for predictive analyses based on six 'desiderata'. These desiderata are an effort to clarify what criteria a good predictive theory of statistics should satisfy.
Mathematical Themes In Economics, Machine Learning, And Bioinformatics, Matt Bogard
Mathematical Themes In Economics, Machine Learning, And Bioinformatics, Matt Bogard
Economics Faculty Publications
Graduate students in economics are often introduced to some very useful mathematical tools that many outside the discipline may not associate with training in economics. This essay looks at some of these tools and concepts, including constrained optimization, separating hyperplanes, supporting hyperplanes, and ‘duality.’ Applications of these tools are explored including topics from machine learning and bioinformatics.
Sustainable Agriculture Bibliography, Matt Bogard
Sustainable Agriculture Bibliography, Matt Bogard
Agriculture Department Seminar Series
An annotated bibliography related to the sustainability of biotechnology and pharmaceutical technologies used in modern agriculture.
Item Order Effects On Attitude Measures, Pei-Hua Chen
Item Order Effects On Attitude Measures, Pei-Hua Chen
Electronic Theses and Dissertations
The purpose of this dissertation was to examine the effects of altered item order on attitude measures for both computerized adaptive and conventional survey formats. Based on items modified from a dissertation/thesis completion survey (Green & Kluever, 1997) with three scales, three survey versions were generated with items ordered by difficulty as hard-to-easy (H-E), easy-to-hard (E-H), and five medium trait level items presented first followed by randomly ordered items (M-R) for conventional survey format. Significant differences in item difficulty and item discrimination were found for two of the three scales. Differences in scale reliability were detected for the procrastination and …
Using R, Matt Bogard
Using R, Matt Bogard
Economics Faculty Publications
R is a statistical programming language with a command line interface that is becoming more and more popular every day. I have used R for data visualization, data mining/machine learning, as well as social network analysis. Initially embraced largely in academia, R is becoming the software of choice in various corporate settings.
Using Twitter To Demonstrate Basic Concepts From Network Analysis, Matt Bogard
Using Twitter To Demonstrate Basic Concepts From Network Analysis, Matt Bogard
Economics Faculty Publications
Social network analysis focuses on finding patterns in interactions between people or entities. These patterns may be described in the form of a network. Network analysis in general has many applications including models of student integration and persistence, business to business supply chains, terrorist cells, or analysis of social media such as Facebook and Twitter. This presentation provides a reference for basic concepts from social network analysis with examples using tweets from Twitter.
Noncompliance With Public Health Service (Phs) Policy On Humane Care And Use Of Laboratory Animals: An Exploratory Analysis, Leah M. Gomez, Kathleen Conlee, Martin Stephens
Noncompliance With Public Health Service (Phs) Policy On Humane Care And Use Of Laboratory Animals: An Exploratory Analysis, Leah M. Gomez, Kathleen Conlee, Martin Stephens
Laboratory Experiments Collection
The National Institutes of Health (NIH) is a major biomedical research-funding body in the United States. Approximately 40% of NIH-funded research involves experimentation on nonhuman animals (Monastersky, 2008). Institutions that conduct animal research with NIH funds must adhere to the Public Health Service (PHS) care and use standards of the Office of Laboratory Animal Welfare (OLAW, 2002a). Institutions deviating significantly from the PHS’s animal care and use standards must report these incidents to the NIH’s OLAW. This study is an exploratory analysis of all the significant deviations reported by animal-research facilities to OLAW during a 3-month period. The study identifies …
Gronwall-Ouiang-Type Integral Inequalities On Time Scales, Ailian Liu, Martin Bohner
Gronwall-Ouiang-Type Integral Inequalities On Time Scales, Ailian Liu, Martin Bohner
Mathematics and Statistics Faculty Research & Creative Works
We present several Gronwall-OuIang-type integral inequalities on time scales. Firstly, an OuIang inequality on time scales is discussed. Then we extend the Gronwall-type inequalities to multiple integrals. Some special cases of our results contain continuous Gronwall-type inequalities and their discrete analogues. Several examples are included to illustrate our results at the end.
Weyl-Titchmarsh Theory For Hamiltonian Dynamic Systems, Shurong Sun, Shaozhu Chen, Martin Bohner
Weyl-Titchmarsh Theory For Hamiltonian Dynamic Systems, Shurong Sun, Shaozhu Chen, Martin Bohner
Mathematics and Statistics Faculty Research & Creative Works
We establish the Weyl-Titchmarsh theory for singular linear Hamiltonian dynamic systems on a time scale T , which allows one to treat both continuous and discrete linear Hamiltonian systems as special cases for T= ℝ and T= ℤ within one theory and to explain the discrepancies between these two theories. This paper extends the Weyl-Titchmarsh theory and provides a foundation for studying spectral theory of Hamiltonian dynamic systems. These investigations are part of a larger program which includes the following: (i) M(λ) theory for singular Hamiltonian systems, (ii) on the spectrum of Hamiltonian systems, (iii) on boundary value problems for …
Ua56/1 Fact Book, Wku Institutional Research
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?, Jason R. W. Merrick, Laura A. Mclay
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, Stephanie Wren
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, Rachel Kast
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, Joaquin Riviera, Yi Li
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, Caixia Xu
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.
Confidence Intervals In Survival Analysis, Tan Shay Kee
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 …
Bayesian Nonparametric Regression With A Flexible Error Term Distribution, Courtney Marie Barnes
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, Angel De Jesus Davalos
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.
Mixture Model Clustering For Very Large Data Sets., Leong Siow Hoo
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 …
Detecting Outliers And Influential Observations In Survival Model., Nor Akmal Md Noh
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 …
A Spline Kernel Based Smoothing Algorithm : A Comparison Of Methods With A Spatiotemporal Application To Global Climate Fluctuations, Derek Daniel Cyr
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, Katerina G. Tsakiri
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, Kim A. S. Factor, Larry J. Langley
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 …
A Mobile Intelligent Interruption Management System, Sina Zulkernain, Praveen Madiraju, Sheikh Iqbal Ahamed, Karl Stamm
A Mobile Intelligent Interruption Management System, Sina Zulkernain, Praveen Madiraju, Sheikh Iqbal Ahamed, Karl Stamm
Mathematics, Statistics and Computer Science Faculty Research and Publications
Mobile phones have become the most hated device that people cannot live without. For its primary usage as a communication device, it has surpassed any other medium. But it comes with a high price, interruption, anywhere anytime. These unwanted interruptions cause loss of productivity and also mostly not beneficial to the immediate task at hand, and moving them few minutes into the future can increase productivity. Considering receivers unavailability, it is possible to manage cell phone disruptions using advanced features like sensing capability, ubiquitous computing and context aware systems. This paper proposes the architecture of a system named Mobile Intelligent …
Local Out-Tournaments With Upset Tournament Strong Components I: Full And Equal {0,1}-Matrix Ranks, Kim A. S. Factor, Rebecca M. Kohler, Jason M. Derby
Local Out-Tournaments With Upset Tournament Strong Components I: Full And Equal {0,1}-Matrix Ranks, Kim A. S. Factor, Rebecca M. Kohler, Jason M. Derby
Mathematics, Statistics and Computer Science Faculty Research and Publications
A digraph D is a local out-tournament if the outset of every vertex is a tournament. Here, we use local out-tournaments, whose strong components are upset tournaments, to explore the corresponding ranks of the adjacency matrices. Of specific interest is the out-tournament whose adjacency matrix has boolean, nonnegative integer, term, and real rank all equal to the number of vertices, n. Corresponding results for biclique covers and partitions of the digraph are provided.
Digraphs With Isomorphic Underlying And Domination Graphs: Pairs Of Paths, Kim A. S. Factor, Larry J. Langley
Digraphs With Isomorphic Underlying And Domination Graphs: 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 thc vertex set of D and edge uv ϵ E (dom (D)) whenever (u, z) ϵ A (D) or (v, z) ϵ A (D) for any other vertex z ϵ A (D). Here, we consider directed graphs whose underlying graphs are isomorphic to their domination graphs. Specifically, digraphs are completely characterized where UGc (D) is the union of two disjoint paths.
Lower Semimodular Inverse Semigroups, Ii, Peter R. Jones, Kyeong Hee Cheong
Lower Semimodular Inverse Semigroups, Ii, Peter R. Jones, Kyeong Hee Cheong
Mathematics, Statistics and Computer Science Faculty Research and Publications
The authors’ description of the inverse semigroups S for which the lattice ℒℱ(S) of full inverse subsemigroups is lower semimodular is used to describe those for which (a) the lattice ℒ(S) of all inverse subsemigroups or (b) the lattice �o(S) of convex inverse subsemigroups has that property. In each case, we show that this occurs if and only if the entire lattice is a subdirect product of ℒℱ(S) with ℒ(E S ), or �o(E S ), respectively, where E S is the semilattice of idempotents of …
Not Every Co-Existential Map Is Confluent, Paul Bankston
Not Every Co-Existential Map Is Confluent, Paul Bankston
Mathematics, Statistics and Computer Science Faculty Research and Publications
A continuous surjection between compacta is co-existential if it is the second of two maps whose composition is a standard ultracopower projection. Co-existential maps are always weakly confluent, and are even monotone when the range space is locally connected; so it is a natural question to ask whether they are always confluent. Here we give a negative answer. This is an interesting question, mainly because of the fact that most theorems about confluent maps have parallel versions for co-existential maps---notably, both kinds of maps preserve hereditary indecomposability. Where the known parallels break down is in the question of chainability. It …
Automation Process For Morphometric Analysis Of Volumetric Ct Data From Pulmonary Vasculature In Rats, Rahul Shingrani, Gary S. Krenz, Robert Molthen
Automation Process For Morphometric Analysis Of Volumetric Ct Data From Pulmonary Vasculature In Rats, Rahul Shingrani, Gary S. Krenz, Robert Molthen
Mathematics, Statistics and Computer Science Faculty Research and Publications
With advances in medical imaging scanners, it has become commonplace to generate large multidimensional datasets. These datasets require tools for a rapid, thorough analysis. To address this need, we have developed an automated algorithm for morphometric analysis incorporating A Visualization Workshop computational and image processing libraries for three-dimensional segmentation, vascular tree generation and structural hierarchical ordering with a two-stage numeric optimization procedure for estimating vessel diameters. We combine this new technique with our mathematical models of pulmonary vascular morphology to quantify structural and functional attributes of lung arterial trees. Our physiological studies require repeated measurements of vascular structure to determine …
Improving Accuracy Of Large-Scale Prediction Of Forest Disease Incidence Through Bayesian Data Reconciliation, Ephraim M. Hanks
Improving Accuracy Of Large-Scale Prediction Of Forest Disease Incidence Through Bayesian Data Reconciliation, Ephraim M. Hanks
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Increasing the accuracy of predictions made from ecological data typically involves replacing or replicating the data, but the cost of updating large-scale data sets can be prohibitive. Focusing resources on a small sample of locations from a large, less accurate data set can result in more reliable observations, though on a smaller scale. We present an approach for increasing the accuracy of predictions made from a large-scale eco logical data set through reconciliation with a small, highly accurate data set within a Bayesian hierarchical modeling framework. This approach is illustrated through a study of incidence of eastern spruce dwarf mistletoe …