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Articles 1 - 30 of 59
Full-Text Articles in Physical Sciences and Mathematics
Statistical Graphics: Applications To The R And Gr Methods In Linear Models, Mei Huang Wang
Statistical Graphics: Applications To The R And Gr Methods In Linear Models, Mei Huang Wang
Dissertations
Statistical graphics combine statistics and graphics together to visually display analytical statistical results. They present information in a way that is very easy to understand and, furthermore, they frequently reveal information that is hidden from numerical summaries. Our purpose of this study is to explore the field of statistical graphics by investigating their application to statistical methods in the context of the R and GR methods in linear models. We consider the problems of score selection, R-diagnostics, and comparison of the R- and GR-fits.
We have developed a user friendly program which uses dynamic graphics and a user interface to …
Student Fact Book, Fall 1996, Wright State University, Office Of Student Information Systems, Wright State University
Student Fact Book, Fall 1996, Wright State University, Office Of Student Information Systems, Wright State University
Wright State University Student Fact Books
The student fact book has general demographic information on all students enrolled at Wright State University for Fall Quarter, 1996.
Review Of: Ike Jeanes, Forecast And Solution - A Trilogy For Everyone Grappling With The Nuclear (Pocahontas Press 1996), Drew Schaefer
Review Of: Ike Jeanes, Forecast And Solution - A Trilogy For Everyone Grappling With The Nuclear (Pocahontas Press 1996), Drew Schaefer
RISK: Health, Safety & Environment (1990-2002)
Review of the book: Ike Jeanes, Forecast and Solution - A Trilogy for Everyone Grappling with the Nuclear (Pocahontas Press 1996). Addenda, appendix, figures, front matter, notes, references, tables. ISBN 0-936015-62-4 [800 pp. Cloth $32.00; paper $25.00. P.O. Drawer F, Blacksburg VA 24063-1020.]
Existence And Bifurcation Of The Positive Solutions For A Semilinear Equation With Critical Exponent, Yinbin Deng, Yi Li
Existence And Bifurcation Of The Positive Solutions For A Semilinear Equation With Critical Exponent, Yinbin Deng, Yi Li
Yi Li
In this paper, we consider the semilinear elliptic equation[formula]Forp=2N/(N−2), we show that there exists a positive constantμ*>0 such that (∗)μpossesses at least one solution ifμ∈(0, μ*) and no solutions ifμ>μ*. Furthermore, (∗)μpossesses a unique solution whenμ=μ*, and at least two solutions whenμ∈(0, μ*) and 2<NN⩾6, under some monotonicity conditions onf((1.6)) we show that there exist two constants 0<μ**⩽μ**<μ* such that problem (∗)μ …
Existence And Bifurcation Of The Positive Solutions For A Semilinear Equation With Critical Exponent, Yinbin Deng, Yi Li
Existence And Bifurcation Of The Positive Solutions For A Semilinear Equation With Critical Exponent, Yinbin Deng, Yi Li
Mathematics and Statistics Faculty Publications
In this paper, we consider the semilinear elliptic equation[formula]Forp=2N/(N−2), we show that there exists a positive constantμ*>0 such that (∗)μpossesses at least one solution ifμ∈(0, μ*) and no solutions ifμ>μ*. Furthermore, (∗)μpossesses a unique solution whenμ=μ*, and at least two solutions whenμ∈(0, μ*) and 2<NN⩾6, under some monotonicity conditions onf((1.6)) we show that there exist two constants 0<μ**⩽μ**<μ* such that problem (∗)μ …
Some Applications Of Sophisticated Mathematics To Randomized Computing, Ronald I. Greenberg
Some Applications Of Sophisticated Mathematics To Randomized Computing, Ronald I. Greenberg
Computer Science: Faculty Publications and Other Works
No abstract provided.
Self-Consistency: A Fundamental Concept In Statistics, Thaddeus Tarpey, Bernard Flury
Self-Consistency: A Fundamental Concept In Statistics, Thaddeus Tarpey, Bernard Flury
Mathematics and Statistics Faculty Publications
The term ''self-consistency'' was introduced in 1989 by Hastie and Stuetzle to describe the property that each point on a smooth curve or surface is the mean of all points that project orthogonally onto it. We generalize this concept to self-consistent random vectors: a random vector Y is self-consistent for X if E[X|Y] = Y almost surely. This allows us to construct a unified theoretical basis for principal components, principal curves and surfaces, principal points, principal variables, principal modes of variation and other statistical methods. We provide some general results on self-consistent random variables, give …
A New Soft Tissue Analysis : To Establish Facial Esthetic Norms In Young Adult Females, Anne Béress
A New Soft Tissue Analysis : To Establish Facial Esthetic Norms In Young Adult Females, Anne Béress
Loma Linda University Electronic Theses, Dissertations & Projects
Two hundred and fifty-five articles, books, and masters theses were reviewed for the most frequently applied soft tissue measurements in the literature in order to develop a new soft tissue analysis computer program that includes established soft tissue measurements and the newly developed globe analysis. A meta analysis of 20 normal occlusion studies, was performed to obtain mean values and standard deviations to form a large sample size. Inclusion criteria for articles in the meta analysis were normal occlusion, no orthodontic treatment, pleasing faces, statement on age, race, and lip position of the population. For the lateral view, angular and …
Optimality And Construction Of Designs With Generalized Group Divisible Structure, Sudesh K. Srivastav
Optimality And Construction Of Designs With Generalized Group Divisible Structure, Sudesh K. Srivastav
Mathematics & Statistics Theses & Dissertations
This thesis is an investigation of the optimality and construction problems attendant to the assignment of v treatments to experimental units in b blocks of size k, paying special attention to settings for which equal replication of the treatments is not possible. The model is that of one way elimination of heterogeneity, in which the expectation of an observation on treatment i in block j is Ti + βj (treatment effect + block effect), where Ti and βj are unknown constants, 1 ≤ i ≤ v and 1 ≤ j ≤ b. All observations are assumed to …
Methodological And Substantive Issues In Substance Abuse Prevention Research, C. Anderson Johnson, John W. Farquhar, Steve Sussman
Methodological And Substantive Issues In Substance Abuse Prevention Research, C. Anderson Johnson, John W. Farquhar, Steve Sussman
CGU Faculty Publications and Research
This article summarizes current issues in drug abuse prevention research through integration of other articles in this journal and by heeding historical trends in prevention science. Recommendations are made for future research directions. For prevention to advance, iterative processes are needed involving both quasi-experimental and experimental designs and involving both small, simple units and large, complex, interactive units. Accuracy of measurement and replication are of paramount importance.
Random Cayley Maps, Michelle Schultz
Random Cayley Maps, Michelle Schultz
Dissertations
Determining the orientable surfaces on which a given graph can be imbedded is the central problem of topological graph theory. The natural setting for studying this problem is random topological graph theory, where a probability model is defined on the space of all labeled 2-cell imbeddings of a connected graph. The major focus of this dissertation is the study of Cayley maps in the setting of random topological graph theory.
A Cayley graph provides a representation of a finite group and a fixed generating set for the group. A Cayley map is an imbedding of a Cayley graph whose vertex …
Adaptive Density Estimation Based On The Mode Existence Test, Nizar Sami Jawhar
Adaptive Density Estimation Based On The Mode Existence Test, Nizar Sami Jawhar
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
The kernel persists as the most useful tool for density estimation. Although, in general, fixed kernel estimates have proven superior to results of available variable kernel estimators, Minnotte's mode tree and mode existence test give us newfound hope of producing a useful adaptive kernel estimator that triumphs when the fixed kernel methods fail. It improves on the fixed kernel in multimodal distributions where the size of modes is unequal, and where the degree of separation of modes varies. When these latter conditions exist, they present a serious challenge to the best of fixed kernel density estimators. Capitalizing on the work …
An International Study Of Intensity In Talented Teenagers Using The Overexcitability Questionnaire (Oeq), John Fraas, Jane Piirto, Geri Cassone, Cheryl Ackerman
An International Study Of Intensity In Talented Teenagers Using The Overexcitability Questionnaire (Oeq), John Fraas, Jane Piirto, Geri Cassone, Cheryl Ackerman
John W. Fraas
No abstract provided.
Wavelet Nonparametric Regression With Dependent Data, Chengjie Xiong, George A. Milliken
Wavelet Nonparametric Regression With Dependent Data, Chengjie Xiong, George A. Milliken
Conference on Applied Statistics in Agriculture
Estimation of the regression function has many applications in agriculture and industry. Usually, the regression function is assumed a known functional form which depends on unknown parameters. Nonparametric regression theory makes no such assumption and often uses some kernel functions to form the so-called Watson Nadaraya type estimators. Such estimators were extensively studied by Watson (1964), Nadaraya (1964, 1989) and Collomb (1981, 1985). When the data are independent, these estimators have nice asymptotic convergence properties. When the data are dependent, Gyorfi et al (1989) gave some large sample properties for the Watson-Nadaraya estimators. In this paper, the recently developed theory …
Validity Of 95% T-Confidence Intervals Under Some Transect Sampling Strategies, Stephen N. Sly, Jeffrey S. Pontius, James J. Higgins
Validity Of 95% T-Confidence Intervals Under Some Transect Sampling Strategies, Stephen N. Sly, Jeffrey S. Pontius, James J. Higgins
Conference on Applied Statistics in Agriculture
Soil pH data were used to assess the capture rates of 95 % t-confidence intervals based on five different transect sampling strategies. Two different sampling methods were considered, "deterministic" and "two-stage simple random sampling". The data used were pH readings at 15 and 30 centimeter depths from two local agricultural fields in the Manhattan, Kansas area. The data provided three distinct populations with three different distributions - skewed left, symmetric, and bimodal. The total number of transects randomly sampled was 2, 5, and 10. The total number of points sampled along each transect was 2, 7 and 14. The 95% …
Designing Speech Interface Applications For Acquisition Of Agricultural Information, Jeffrey Willers, Susan Bridges, Xiaofeng Ma, James Mckinion, Jean Liang
Designing Speech Interface Applications For Acquisition Of Agricultural Information, Jeffrey Willers, Susan Bridges, Xiaofeng Ma, James Mckinion, Jean Liang
Conference on Applied Statistics in Agriculture
It will be argued that customary software design strategies, by themselves, fall short when designing speech recognition applications. Concepts of experimental design and analysis are also necessary for developing speech interface software. This study demonstrates that these tools can be advantageous to the software developer, especially if the prototype methodology model of software development is applied. A case study for the problem of developing a speech interface for collecting, or mapping, information on cotton plant growth is presented. The acquisition of cotton plant map data is a 'hands and eyes' busy task that requires considerable investment to record and convert …
A New Approach To Teaching Natural Resource Sampling, Kenneth M. Portier, Loukas G. Arvanitis, Daniel Brackett
A New Approach To Teaching Natural Resource Sampling, Kenneth M. Portier, Loukas G. Arvanitis, Daniel Brackett
Conference on Applied Statistics in Agriculture
A basic undergraduate course in statistics is often not adequate for students in renewable natural resource programs such as wildlife, forestry, fisheries, and related subjects. A strong foundation in the basics of sampling in time and space of forest, vegetation, wildlife and fish populations is needed. A brief account of our experience in teaching such a course over the last three years along with progress on developing course-related material and activities is reported. This includes the development of: 1) computer-based simulations; 2) in-class participation simulations to illustrate the basic concepts of sampling in space and time; 3) exercises to introduce …
Experimentation Science: A Process Approach For The Complete Design Of An Experiment, D. D. Kratzer, K. A. Ash
Experimentation Science: A Process Approach For The Complete Design Of An Experiment, D. D. Kratzer, K. A. Ash
Conference on Applied Statistics in Agriculture
Experimentation Science is introduced as a process through which the necessary steps of experimental design are all sufficiently addressed. Experimentation Science is defined as a nearly linear process of objective formulation, selection of experimentation unit and decision variable(s), deciding treatment, design and error structure, defining the randomization, statistical analyses and decision procedures, outlining quality control procedures for data collection, and finally analysis, presentation and interpretation of results. The protocol description form (PDF) is introduced as an instrument to guide the implementation and documentation of the Experimentation Science process.
Markov Chain Monte Carlo Methods For Modeling The Spatial Pattern Of Disease Spread In Bell Pepper, Jonathan M. Graham
Markov Chain Monte Carlo Methods For Modeling The Spatial Pattern Of Disease Spread In Bell Pepper, Jonathan M. Graham
Conference on Applied Statistics in Agriculture
With exponential family models for dependent data, such as the autologistic model for binary spatial lattice data, maximum likelihood estimates can be obtained using Markov chain sampling methods by simulating an ergodic Markov chain which converges weakly to the equilibrium distribution of the model. This Markov chain Monte Carlo maximum likelihood (MCMCML) procedure provides a competitor to the usual pseudolikelihood estimation method often used for modeling discrete lattice data. Within this MCMCML framework, it is also possible to conduct formal inference using MCMC analogues to the usual likelihood ratio, Wald, and Lagrange multiplier tests, for which the asymptotic distributions are …
Confidence Intervals For The Coefficient Of Variation, Mark E. Payton
Confidence Intervals For The Coefficient Of Variation, Mark E. Payton
Conference on Applied Statistics in Agriculture
The coefficient of variation (CV), defined as the ratio of the standard deviation to the mean, is often used in experimental situations. The exact distribution of the sample CV from a normally distributed population is complicated and obtaining a confidence interval for the population CV in this situation would require using the non-central t distribution and sequential techniques (Koopmans, et al., 1964). This paper explores the use of approximate distributions in determining confidence limits for the CV. The gamma distribution is used to model data appropriate for the calculation of the CV. A Monte Carlo simulation is performed to evaluate …
Estimation Of Kinetic Parameters Associated With Nutrient Uptake By An Intact Plant Root System, Edward Gbur, Craig Beyrouty
Estimation Of Kinetic Parameters Associated With Nutrient Uptake By An Intact Plant Root System, Edward Gbur, Craig Beyrouty
Conference on Applied Statistics in Agriculture
Several mechanistic models have been developed for the prediction of nutrient uptake at low concentrations from the soil by a plant root system. Claassen and Barber (1974 Plant Physiology 54, 564-568; 1976 Agronomy Journal 68, 961-964) presented an experimental procedure to obtain data from intact plants to fit an ion depletion curve and used the data in a model which they developed to predict nutrient uptake. Their model assumed that nutrient absorption from the soil solution followed Michaelis-Menten kinetics. In this paper, we develop a stochastic version of the Claassen-Barber model and illustrate its application to the estimation of the …
Analysis Of Unbalanced Mixed Model Data: Traditional Anova Versus Contemporary Methods, Ramon C. Littell
Analysis Of Unbalanced Mixed Model Data: Traditional Anova Versus Contemporary Methods, Ramon C. Littell
Conference on Applied Statistics in Agriculture
Analysis of unbalanced data and analysis of mixed model data are important topics of statistical discussion. Analysis of unbalanced data with fixed effects gives rise to the different types of sums of squares in analysis of variance. Mixed model riata raises issues of determining appropriate error terms for test statistics and standard errors Clf estimates. The situation is even more difficult when the two topics occur together, resulting in unbalanced mixed model data. These problems have plagued users ofPROC GLM in the SAS System. Now, with PROC MIXED available, some of the problems are resolved while others remain. This paper …
Analysis Of Proportions From Split-Plot And Repeated Measures Experiments, Kenneth J. Koehler
Analysis Of Proportions From Split-Plot And Repeated Measures Experiments, Kenneth J. Koehler
Conference on Applied Statistics in Agriculture
Several methods for analyzing proportions from split-plot and repeated measures experiments are illustrated and compared. One approach simply uses analysis of variance for the usual linear mixed model fit to split-plot and repeated measures experiments. Alternatively, logistic regression analysis is considered and a so-called robust estimate of the covariance matrix is used to adjust for possible correlations among responses. Finally, a quasi-likelihood approach to logistic regression analysis that requires more explicit specification of the covariance structure for the observed proportions is considered. These methods are illustrated with the analyses of data from a repeated measures study of acorn consumption by …
Estimation Of Cardinal Temperatures In Germination Data Analysis, Cindy Roche, Bahman Shafii, Donald C. Thill, William J. Price
Estimation Of Cardinal Temperatures In Germination Data Analysis, Cindy Roche, Bahman Shafii, Donald C. Thill, William J. Price
Conference on Applied Statistics in Agriculture
Seed germination is a complex biological process which is influenced by various environmental and genetic factors. The effects of temperature on plant development are the basis for models used to predict the timing of germination. Estimation of the cardinal temperatures, including base, optimum, and maximum, is essential because rate of development increases between base and optimum, decreases between optimum and maximum, and ceases above the maximum and below the base temperature. Nonlinear growth curves can be specified to model the time course of germination at various temperatures. Quantiles of such models are regressed on temperature to estimate cardinal quantities. Bootstrap …
Long-Term Tillage Effects On Continuous Corn Yields, T. B. Bailey, J. B. Swan, R L. Higgs, W. H. Paulson
Long-Term Tillage Effects On Continuous Corn Yields, T. B. Bailey, J. B. Swan, R L. Higgs, W. H. Paulson
Conference on Applied Statistics in Agriculture
Long-term comparisons of alternative tillage systems are needed to evaluate their effect on corn (Zea mays L.) yield under the variable temperature and rainfall conditions of the Corn Belt. Our objective was to evaluate long-term effects of alternative tillage systems on corn growth and yield on low organic matter silt loam soils. The effect of no-tillage (NT), chisel plow (CP), and moldboard plow (MP) treatments on plant density and grain yield was measured from 1981 through 1990 on Palsgrove and Rozetta silt loam (fine-silty, mixed mesic Typic Hapludalfs) soils. Tillage treatments were randomly allocated to plots in 1981 …
An Introduction To Generalized Linear Mixed Models, Charles E. Mcculloch
An Introduction To Generalized Linear Mixed Models, Charles E. Mcculloch
Conference on Applied Statistics in Agriculture
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accommodation of non-normally distributed responses, specification of a possibly non-linear link between the mean of the response and the predictors, and allowance for some forms of correlation in the data. As such, GLMMs have broad utility and are of great practical importance. Two special cases of the GLMM are the linear mixed model (LMM) and the generalized linear model (GLM). Despite the utility of such models, their use has been limited due to the lack of reliable, well-tested estimation and testing methods. I first describe and …
Editor's Preface, Table Of Contents, And List Of Attendees, George A. Milliken
Editor's Preface, Table Of Contents, And List Of Attendees, George A. Milliken
Conference on Applied Statistics in Agriculture
These proceedings contain papers presented in the eighth annual Kansas State University Conference on Applied Statistics in Agriculture, held in Manhattan, Kansas, April 28-30, 1996..
Jury Responsibility In Capital Sentencing: An Empirical Study, Theodore Eisenberg, Stephen P. Garvey, Martin T. Wells
Jury Responsibility In Capital Sentencing: An Empirical Study, Theodore Eisenberg, Stephen P. Garvey, Martin T. Wells
Cornell Law Faculty Publications
The law allows executioners to deny responsibility for what they have done by making it possible for them to believe they have not done it. The law treats members of capital sentencing juries quite differently. It seeks to ensure that they feel responsible for sentencing a defendant to death. This differential treatment rests on a presumed link between a capital sentencer's willingness to accept responsibility for the sentence she imposes and the accuracy and reliability of that sentence. Using interviews of 153 jurors who sat in South Carolina capital cases, this article examines empirically whether capital sentencing jurors assume responsibility …
Litigation Outcomes In State And Federal Courts: A Statistical Portrait, Theodore Eisenberg, John Goerdt, Brian Ostrom, David Rottman
Litigation Outcomes In State And Federal Courts: A Statistical Portrait, Theodore Eisenberg, John Goerdt, Brian Ostrom, David Rottman
Cornell Law Faculty Publications
"U.S. Juries Grow Tougher on Plaintiffs in Lawsuits," the New York Times page-one headline reads. The story details how, in 1992, plaintiffs won 52 percent of the personal injury cases decided by jury verdicts, a decline from the 63 percent plaintiff success rate in 1989. The sound-byte explanations follow, including the notion that juries have learned that they, as part of the general population, ultimately pay the costs of high verdicts. Similar stories, reporting both increases and decreases in jury award levels, regularly make headlines. Jury Verdict Research, Inc. (JVR), a commercial service that sells case outcome information, often is …
Stability Analysis Of A Model For The Defect Structure Of Yba2cu3ox, Gregory Kozlowski, Tom Svobodny
Stability Analysis Of A Model For The Defect Structure Of Yba2cu3ox, Gregory Kozlowski, Tom Svobodny
Physics Faculty Publications
Unusual microstructures of YBa2Cu3Ox (123) crystals have been observed. These structures have been shown to pass very high transport currents. A model of the solidification of 123 from a melt with Y2BaCuO5 (211) inclusions indicates that the stability of the 123 interface can depend on the sizes of the 211 inclusions. The observed formations are interpreted in the light of this instability.