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Articles 1 - 30 of 66
Full-Text Articles in Statistics and Probability
Numerical And Asymptotical Study Of Three-Dimensional Wave Packets In A Compressible Boundary Layer, Eric Forgoston, Michael Viergutz, Anatoli Tumin
Numerical And Asymptotical Study Of Three-Dimensional Wave Packets In A Compressible Boundary Layer, Eric Forgoston, Michael Viergutz, Anatoli Tumin
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
A three-dimensional wave packet generated by a local disturbance in a two-dimensional hypersonic boundary layer flow is studied with the aid of the previously solved initialvalue problem. The solution can be presented as a sum of modes consisting of continuous and discrete spectra of temporal stability theory. Two discrete modes, known as Mode S and Mode F, are of interest in high-speed flows since they may be involved in a laminar-turbulent transition scenario. The continuous and discrete spectra are analyzed numerically for a hypersonic flow. A comprehensive study of the spectrum is performed, including Reynolds number, Mach number and temperature …
Topology Of Attractors From Two-Piece Expanding Maps, Youngna Choi
Topology Of Attractors From Two-Piece Expanding Maps, Youngna Choi
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
In this paper we study the topology of the invariant sets derived from two-piece expanding maps. We classify the conditions under which the invariant sets are topological attractors, and show that the set of attractors is open and dense in the set of invariant sets derived by two-piece expanding maps.
Ex Ante Choices Of Law And Forum: An Empirical Analysis Of Corporate Merger Agreements, Theodore Eisenberg, Geoffrey P. Miller
Ex Ante Choices Of Law And Forum: An Empirical Analysis Of Corporate Merger Agreements, Theodore Eisenberg, Geoffrey P. Miller
Cornell Law Faculty Publications
Legal scholars have focused much attention on the incorporation puzzle—why business corporations so heavily favor Delaware as the site of incorporation. This paper suggests that the focus on the incorporation decision overlooks a broader but intimately related set of questions. The choice of Delaware as a situs of incorporation is, effectively, a choice of law decision. A company electing to charter in Delaware selects Delaware law (and authorizes Delaware courts to adjudicate legal disputes) regarding the allocation of governance authority within the firm. In this sense, the incorporation decision is fundamentally similar to any setting in which a company selects …
A Conversation With Harry Martz, Paul H. Kvam
A Conversation With Harry Martz, Paul H. Kvam
Department of Math & Statistics Faculty Publications
Harry F. Martz was born June 16, 1942 and grew up in Cumberland, Maryland. He received a Bachelor of Science degree in mathematics (with a minor in physics) from Frostburg State University in 1964, and earned a Ph.D. in statistics at Virginia Polytechnic Institute and State University in 1968. He started his statistics career at Texas Tech University's Department of Industrial Engineering and Statistics right after graduation. In 1978, he joined the technical staff at Los Alamos National Laboratory (LANL) in Los Alamos, New Mexico after first working as Full Professor in the Department of Industrial Engineering at Utah State …
Allometric Extension For Multivariate Regression Models, Thaddeus Tarpey, Christopher T. Ivey
Allometric Extension For Multivariate Regression Models, Thaddeus Tarpey, Christopher T. Ivey
Mathematics and Statistics Faculty Publications
In multivariate regression, interest lies on how the response vector depends on a set of covariates. A multivariate regression model is proposed where the covariates explain variation in the response only in the direction of the first principal component axis. This model is not only parsimonious, but it provides an easy interpretation in allometric growth studies where the first principal component of the log-transformed data corresponds to constants of allometric growth. The proposed model naturally generalizes the two–group allometric extension model to the situation where groups differ according to a set of covariates. A bootstrap test for the model is …
A Mathematical Regression Of The U.S. Gross Private Domestic Investment 1959-2001, Byron E. Bell
A Mathematical Regression Of The U.S. Gross Private Domestic Investment 1959-2001, Byron E. Bell
Byron E. Bell
SUMMARY OF PROJECT What did I do? A study of the role the U.S. stock markets and money markets have possibly played in the Gross Private Domestic Investment (GPDI) of the United States from the year 1959 to the year 2001 and I created a Multiple Linear Regression Model (MLRM).
Theory Of Effectiveness Measurement, Richard K. Bullock
Theory Of Effectiveness Measurement, Richard K. Bullock
Theses and Dissertations
Effectiveness measures provide decision makers feedback on the impact of deliberate actions and affect critical issues such as allocation of scarce resources, as well as whether to maintain or change existing strategy. Currently, however, there is no formal foundation for formulating effectiveness measures. This research presents a new framework for effectiveness measurement from both a theoretical and practical view. First, accepted effects-based principles, as well as fundamental measurement concepts are combined into a general, domain independent, effectiveness measurement methodology. This is accomplished by defining effectiveness measurement as the difference, or conceptual distance from a given system state to some reference …
Statistical Approach To Background Subtraction For Production Of High-Quality Silhouettes For Human Gait Recognition, Jennifer J. Samler
Statistical Approach To Background Subtraction For Production Of High-Quality Silhouettes For Human Gait Recognition, Jennifer J. Samler
Theses and Dissertations
This thesis uses a background subtraction to produce high-quality silhouettes for use in human identification by human gait recognition, an identification method which does not require contact with an individual and which can be done from a distance. A statistical method which reduces the noise level is employed resulting in cleaner silhouettes which facilitate identification. The thesis starts with gathering video data of individuals walking normally across a background scene. From there the video is converted into a sequence of images that are stored as joint photographic experts group (jpeg) files. The background is subtracted from each image using a …
Incentive Awards To Class Action Plaintiffs: An Empirical Study, Theodore Eisenberg, Geoffrey P. Miller
Incentive Awards To Class Action Plaintiffs: An Empirical Study, Theodore Eisenberg, Geoffrey P. Miller
Cornell Law Faculty Publications
Incentive awards to representative plaintiffs in class actions have been the focus of recent law reform efforts and have generated inconsistent case law. But little is known about such awards. This study of 374 opinions from 1993 to 2002 finds that awards were granted in about 28 percent of settled class actions. The rate of awards varied by case category as follows: consumer credit actions 59 percent, employment discrimination cases 46 percent, antitrust cases 35 percent, securities cases 24 percent (before the Private Securities Litigation Reform Act of 1995 limited awards), and corporate and mass tort actions less than 10 …
Efficient Unbiased Estimating Equations For Analyzing Structured Correlation Matrices, Yihao Deng
Efficient Unbiased Estimating Equations For Analyzing Structured Correlation Matrices, Yihao Deng
Mathematics & Statistics Theses & Dissertations
Analysis of dependent continuous and discrete data has become an active area of research. For normal data, correlations fully quantify the dependence. And historically, maximum likelihood method has been very successful to estimate the correlations and unbiased estimating equation approach has become a popular alternative when there may be a departure from normality. In this thesis we show that the optimal unbiased estimating equation coincides with the likelihood equations for normal data. We then introduce a general class of weighted unbiased estimating equations to estimate parameters in a structured correlation matrix. We derive expressions for asymptotic covariance of the estimates, …
Ancova: A Robust Omnibus Test Based On Selected Design Points, Rand R. Wilcox
Ancova: A Robust Omnibus Test Based On Selected Design Points, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Many robust analogs of the classic analysis of covariance method have been proposed. One approach, when comparing two independent groups, uses selected design points and then compares the groups at each design point using some robust method for comparing measures of location. So, if K design points are of interest, K tests are performed. There are rather obvious ways of performing, instead, an omnibus test that for all K points, no differences between the groups exist. One of the main results here is that several variations of these methods can perform very poorly in simulations. An alternative approach, based in …
The Effect On Type I Error And Power Of Various Methods Of Resolving Ties For Six Distribution-Free Tests Of Location, Bruce R. Fay
The Effect On Type I Error And Power Of Various Methods Of Resolving Ties For Six Distribution-Free Tests Of Location, Bruce R. Fay
Journal of Modern Applied Statistical Methods
The impact on Type I error robustness and power for nine different methods of resolving ties was assessed for six distribution-free statistics with four empirical data sets using Monte Carlo techniques. These statistics share an underlying assumption of population continuity such that samples are assumed to have no equal data values (no zero difference–scores, no tied ranks). The best results across all tests and combinations of simulation parameters were obtained by randomly resolving ties, although there were exceptions. The method of dropping ties and reducing the sample size performed poorly.
Limitations Of The Analysis Of Variance, Phillip I. Good, Clifford E. Lunneborg
Limitations Of The Analysis Of Variance, Phillip I. Good, Clifford E. Lunneborg
Journal of Modern Applied Statistical Methods
Conditions under which the analysis of variance will yield inexact p-values or would be inferior in power to a permutation test are investigated. The findings for the one-way design are consistent with and extend those of Miller (1980).
Multiple Comparison Procedures, Trimmed Means And Transformed Statistics, Rhonda K. Kowalchuk, H. J. Keselman, Rand R. Wilcox, James Algina, James Algina, James Algina
Multiple Comparison Procedures, Trimmed Means And Transformed Statistics, Rhonda K. Kowalchuk, H. J. Keselman, Rand R. Wilcox, James Algina, James Algina, James Algina
Journal of Modern Applied Statistical Methods
A modification to testing pairwise comparisons that may provide better control of Type I errors in the presence of non-normality is to use a preliminary test for symmetry which determines whether data should be trimmed symmetrically or asymmetrically. Several pairwise MCPs were investigated, employing a test of symmetry with a number of heteroscedastic test statistics that used trimmed means and Winsorized variances. Results showed improved Type I error control than competing robust statistics.
Understanding Eurasian Convergence: Application Of Kohonen Self-Organizing Maps, Joel I. Deichmann, Abdolreza Eshghi, Dominique Haughton, Selin Sayek, Nicholas Teebagy, Heikki Topi
Understanding Eurasian Convergence: Application Of Kohonen Self-Organizing Maps, Joel I. Deichmann, Abdolreza Eshghi, Dominique Haughton, Selin Sayek, Nicholas Teebagy, Heikki Topi
Journal of Modern Applied Statistical Methods
Kohonen self-organizing maps (SOMs) are employed to examine economic and social convergence of Eurasian countries based on a set of twenty-eight socio-economic measures. A core of European Union states is identified that provides a benchmark against which convergence of post-socialist transition economies may be judged. The Central European Visegrád countries and Baltics show the greatest economic convergence to Western Europe, while other states form clusters that lag behind. Initial conditions on the social dimension can either facilitate or constrain economic convergence, as discovered in Central Europe vis-à-vis the Central Asian Republics. Disquiet in the convergence literature is resolved by providing …
Entropy Criterion In Logistic Regression And Shapley Value Of Predictors, Stan Lipovetsky
Entropy Criterion In Logistic Regression And Shapley Value Of Predictors, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Entropy criterion is used for constructing a binary response regression model with a logistic link. This approach yields a logistic model with coefficients proportional to the coefficients of linear regression. Based on this property, the Shapley value estimation of predictors’ contribution is applied for obtaining robust coefficients of the linear aggregate adjusted to the logistic model. This procedure produces a logistic regression with interpretable coefficients robust to multicollinearity. Numerical results demonstrate theoretical and practical advantages of the entropy-logistic regression.
Choosing Smoothing Parameters For Exponential Smoothing: Minimizing Sums Of Squared Versus Sums Of Absolute Errors, Terry E. Dielman
Choosing Smoothing Parameters For Exponential Smoothing: Minimizing Sums Of Squared Versus Sums Of Absolute Errors, Terry E. Dielman
Journal of Modern Applied Statistical Methods
When choosing smoothing parameters in exponential smoothing, the choice can be made by either minimizing the sum of squared one-step-ahead forecast errors or minimizing the sum of the absolute onestep- ahead forecast errors. In this article, the resulting forecast accuracy is used to compare these two options.
Penalized Splines For Longitudinal Data With An Application In Aids Studies, Hua Liang, Yuanhui Xiao
Penalized Splines For Longitudinal Data With An Application In Aids Studies, Hua Liang, Yuanhui Xiao
Journal of Modern Applied Statistical Methods
A penalized spline approximation is proposed in considering nonparametric regression for longitudinal data. Standard linear mixed-effects modeling can be applied for the estimation. It is relatively simple, efficiently computed, and robust to the smooth parameters selection, which are often encountered when local polynomial and smoothing spline techniques are used to analyze longitudinal data set. The method is extended to time-varying coefficient mixed-effects models. The proposed methods are applied to data from an AIDS clinical study. Biological interpretations and clinical implications are discussed. Simulation studies are done to illustrate the proposed methods.
Analysis Of Type-Ii Progressively Hybrid Censored Competing Risks Data, Debasis Kundu, Avijit Joarder
Analysis Of Type-Ii Progressively Hybrid Censored Competing Risks Data, Debasis Kundu, Avijit Joarder
Journal of Modern Applied Statistical Methods
A Type-II progressively hybrid censoring scheme for competing risks data is introduced, where the experiment terminates at a pre-specified time. The likelihood inference of the unknown parameters is derived under the assumptions that the lifetime distributions of the different causes are independent and exponentially distributed. The maximum likelihood estimators of the unknown parameters are obtained in exact forms. Asymptotic confidence intervals and two bootstrap confidence intervals are also proposed. Bayes estimates and credible intervals of the unknown parameters are obtained under the assumption of gamma priors on the unknown parameters. Different methods have been compared using Monte Carlo simulations. One …
The Efficiency Of Ols In The Presence Of Auto-Correlated Disturbances In Regression Models, Samir Safi, Alexander White
The Efficiency Of Ols In The Presence Of Auto-Correlated Disturbances In Regression Models, Samir Safi, Alexander White
Journal of Modern Applied Statistical Methods
The ordinary least squares (OLS) estimates in the regression model are efficient when the disturbances have mean zero, constant variance, and are uncorrelated. In problems concerning time series, it is often the case that the disturbances are correlated. Using computer simulations, the robustness of various estimators are considered, including estimated generalized least squares. It was found that if the disturbance structure is autoregressive and the dependent variable is nonstochastic and linear or quadratic, the OLS performs nearly as well as its competitors. For other forms of the dependent variable, rules of thumb are presented to guide practitioners in the choice …
Comparison Of Some Simple Estimators Of The Lognormal Parameters Based On Censored Samples, Baklizi Ayman, Mohammed Al-Haj Ebrahem
Comparison Of Some Simple Estimators Of The Lognormal Parameters Based On Censored Samples, Baklizi Ayman, Mohammed Al-Haj Ebrahem
Journal of Modern Applied Statistical Methods
Point estimation of the parameters of the lognormal distribution with censored data is considered. The often employed maximum likelihood estimator does not exist in closed form and iterative methods that require very good starting points are needed. In this article, some techniques of finding closed form estimators to this situation are presented and extended. An extensive simulation study is carried out to investigate and compare the performance of these techniques. The results show that some of them are highly efficient as compared with the maximum likelihood estimator.
Two New Unbiased Point Estimates Of A Population Variance, Matthew E. Elam
Two New Unbiased Point Estimates Of A Population Variance, Matthew E. Elam
Journal of Modern Applied Statistical Methods
Two new unbiased point estimates of an unknown population variance are introduced. They are compared to three known estimates using the mean-square error (MSE). A computer program, which is available for download at http://program.20m.com, is developed for performing calculations for the estimates.
Properties Of Bound Estimators On Treatment Effect Heterogeneity For Binary Outcomes, Edward J. Mascha, Jeffrey M. Albert
Properties Of Bound Estimators On Treatment Effect Heterogeneity For Binary Outcomes, Edward J. Mascha, Jeffrey M. Albert
Journal of Modern Applied Statistical Methods
Variability in individual causal effects, treatment effect heterogeneity (TEH), is important to the interpretation of clinical trial results, regardless of the marginal treatment effect. Unfortunately, it is usually ignored. In the setting of two-arm randomized studies with binary outcomes, there are estimators for bounds on the probability of control success and treatment failure for an individual, or the treatment risk. Here, those bounds were refined and the sampling properties were assessed using simulations of correlated multinomial data via the Dirichlet multinomial. Results indicated low bias and mean squared error. Moderate to high intraclass correlation (ICC) and large numbers of clusters …
A Combined Individuals And Moving Range Control Chart, Michael B. C. Khoo, S. H. Quah, C. K. Ch'ng
A Combined Individuals And Moving Range Control Chart, Michael B. C. Khoo, S. H. Quah, C. K. Ch'ng
Journal of Modern Applied Statistical Methods
An individuals control chart is usually used to monitor shifts in the process mean when it is not possible to form subgroups. The moving range of two successive process measures is used as the basis for estimating the process variability. Similar to the case of the X − R and X − S charts, the individualsmoving range (I-MR) charts are used simultaneously in the monitoring of the process mean and variance respectively for individual observations, requiring maintaining two different charts. In this article, a new approach is suggested where the measurements of both the process mean and variance are plotted …
Variance Estimation And Construction Of Confidence Intervals For Gee Estimator, Shenghai Zhang, Mary E. Thompson
Variance Estimation And Construction Of Confidence Intervals For Gee Estimator, Shenghai Zhang, Mary E. Thompson
Journal of Modern Applied Statistical Methods
The sandwich estimator, also known as the robust covariance matrix estimator, has achieved increasing use in the statistical literature as well as with the growing popularity of generalized estimating equations (GEE). A modified sandwich variance estimator is proposed, and its consistency and efficiency are studied. It is compared with other variance estimators, such as a model based estimator, the sandwich estimator and a corrected sandwich estimator. Confidence intervals for regression parameters based on these estimators are discussed. Simulation studies using clustered data to compare the performance of variance estimators are reported.
The Use Of Hierarchical Ancova In Curriculum Studies, Show-Mann Liou, Chao-Ying Joanne Peng
The Use Of Hierarchical Ancova In Curriculum Studies, Show-Mann Liou, Chao-Ying Joanne Peng
Journal of Modern Applied Statistical Methods
Many educational studies are carried out in intact settings, such as classrooms or groups in which individual data were collected before and after a treatment. Researchers advocate either the use of individual scores as the unit of analysis or class means. Both approaches suffer from conceptual and methodological limitations. In this article, the use of hierarchical ANCOVA for analyzing quasiexperimental data including baseline measures is designed and promoted. It is illustrated with a realworld data set collected from a curriculum study. Results showed that the hierarchical ANCOVA is a conceptually and methodologically sound approach, and is better than ANCOVA based …
A Combined Standard Deviation Based Data Clustering Algorithm, Kuttiannan Thangavel, Durairaj Ashok Kumar
A Combined Standard Deviation Based Data Clustering Algorithm, Kuttiannan Thangavel, Durairaj Ashok Kumar
Journal of Modern Applied Statistical Methods
The clustering problem has been widely studied because it arises in many knowledge management oriented applications. It aims at identifying the distribution of patterns and intrinsic correlations in data sets by partitioning the data points into similarity clusters. Traditional clustering algorithms use distance functions to measure similarity centroid, which subside the influences of data points. Hence, in this article a novel non-distance based clustering algorithm is proposed which uses Combined Standard Deviation (CSD) as measure of similarity. The performance of CSD based K-means approach, called K-CSD clustering algorithm, is tested on synthetic data sets. It compared favorably to widely used …
Jmasm23: Cluster Analysis In Epidemiological Data (Matlab), Andrés M. Alonso
Jmasm23: Cluster Analysis In Epidemiological Data (Matlab), Andrés M. Alonso
Journal of Modern Applied Statistical Methods
Matlab functions for testing the existence of time, space and time-space clusters of disease occurrences are presented. The classical scan test, the Ederer, Myers and Mantel’s test, the Ohno, Aoki and Aoki’s test, and the Knox’s test are considered.
Confidence Intervals On Subsets May Be Misleading, Juliet Popper Shaffer
Confidence Intervals On Subsets May Be Misleading, Juliet Popper Shaffer
Journal of Modern Applied Statistical Methods
No abstract provided.
Statistical Pronouncements V, Jmasm Editors
Statistical Pronouncements V, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.