Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Social and Behavioral Sciences (62)
- Statistical Theory (56)
- Life Sciences (13)
- Agriculture (12)
- Applied Mathematics (12)
-
- Mathematics (8)
- Engineering (6)
- Econometrics (4)
- Economics (4)
- Civil and Environmental Engineering (3)
- Electrical and Computer Engineering (3)
- Mechanical Engineering (3)
- Multivariate Analysis (3)
- Signal Processing (3)
- Agricultural and Resource Economics (2)
- Anthropology (2)
- Biochemical and Biomolecular Engineering (2)
- Business (2)
- Chemical Engineering (2)
- Computational Engineering (2)
- Dynamic Systems (2)
- Environmental Engineering (2)
- Environmental Sciences (2)
- Finance (2)
- Finance and Financial Management (2)
- Heat Transfer, Combustion (2)
- Industrial Engineering (2)
- Institution
- Keyword
-
- Bias (3)
- Confidence interval (3)
- Control chart (3)
- Effect size (3)
- Robustness (3)
-
- Asymptotic behavior (2)
- Calculation (2)
- Euler flows (2)
- Goodness of fit (2)
- Heteroscedasticity (2)
- Least squares (2)
- Multiple regression (2)
- Multiple testing (2)
- Navier-Stokes flows (2)
- Non-normal data (2)
- Robust regression (2)
- Statistics (2)
- Type I error (2)
- Variance (2)
- Viscoelastic flows (2)
- ANOVA (1)
- ANOVA model (1)
- ARIMA (1)
- ARMA spectra (1)
- Acquisition (1)
- Adaptive (1)
- Adaptive estimator (1)
- Age-periodcohort model prediction (1)
- Aggregate output (1)
- Airplanes--Scramjet engines (1)
- Publication
-
- Journal of Modern Applied Statistical Methods (55)
- Conference on Applied Statistics in Agriculture (12)
- Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works (4)
- Mathematics and Statistics Faculty Publications (4)
- Theses and Dissertations (4)
-
- Department of Math & Statistics Faculty Publications (3)
- Dr. Erik Dahlquist (2)
- Industrial and Management Systems Engineering: Instructional Materials (2)
- Lorán Chollete (2)
- Applications and Applied Mathematics: An International Journal (AAM) (1)
- Articles (1)
- Douglas G. Steigerwald (1)
- Dr Babatunde Buraimo (1)
- Faculty Journal Articles (1)
- Masters Theses (1)
- Tony Badrick (1)
- University of Kentucky Doctoral Dissertations (1)
- Yi Li (1)
- Zhao (Tony) Yang, Ph.D. (1)
- Zhengyuan Zhu (1)
- Publication Type
- File Type
Articles 1 - 30 of 99
Full-Text Articles in Applied Statistics
An Optimal Principle In Fluid-Structure Interaction, Bong Jae Chung, Ashuwin Vaidya
An Optimal Principle In Fluid-Structure Interaction, Bong Jae Chung, Ashuwin Vaidya
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
We study the steady terminal orientation of a fore-aft symmetric body as it settles in a viscous fluid. An optimal principle for the settling behavior is discussed based upon entropy production in the system, both in the Stokes limit and the case of near equilibrium states when inertial effects emerge. We show that in the Stokes limit, the entropy production in the system is zero allowing any possible terminal orientation while in the presence of inertia, the particle assumes a horizontal position which coincides with the state of maximum entropy production. Our results are seen to agree well with experimental …
Application Of Dynamic Poisson Models To Japanese Cancer Mortality Data, Shuichi Midorikawa, Etsuo Miyaoka, Bruce Smith
Application Of Dynamic Poisson Models To Japanese Cancer Mortality Data, Shuichi Midorikawa, Etsuo Miyaoka, Bruce Smith
Journal of Modern Applied Statistical Methods
A dynamic Poisson model is used with a Bayesian approach to modeling to predict cancer mortality. The complexity of the posterior distribution prohibits direct evaluation of the posterior, and so parameters are estimated by using a Markov Chain Monte Carlo method. The model is applied to analyze lung and stomach cancer data which have been collected in Japan.
Data Mining Ceo Compensation, Susan M. Adams, Atul Gupta, Dominique M. Haughton, John D. Leeth
Data Mining Ceo Compensation, Susan M. Adams, Atul Gupta, Dominique M. Haughton, John D. Leeth
Journal of Modern Applied Statistical Methods
The need to pre-specify expected interactions between variables is an issue in multiple regression. Theoretical and practical considerations make it impossible to pre-specify all possible interactions. The functional form of the dependent variable on the predictors is unknown in many cases. Two ways are described in which the data mining technique Multivariate Adaptive Regression Splines (MARS) can be utilized: first, to obtain possible improvements in model specification, and second, to test for the robustness of findings from a regression analysis. An empirical illustration is provided to show how MARS can be used for both purposes.
Estimating Explanatory Power In A Simple Regression Model Via Smoothers, Rand R. Wilcox
Estimating Explanatory Power In A Simple Regression Model Via Smoothers, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider the regression model Y = γ(X) + ε , where γ(X) is some conditional measure of location associated with Y , given X. Let Υ̂ be some estimate of Y, given X, and let τ2 (Y) be some measure of variation. Explanatory power is η2 = τ2 (Υ̂) /τ2(Y) . When γ(X) = β0 + β1X and τ2(Y) is the variance of Y , η2 = ρ2 , …
Type I Error Rates Of The Kenward-Roger F-Test For A Split-Plot Design With Missing Values And Non-Normal Data, Miguel A. Padilla, Youngkyoung Min, Guili Zhang
Type I Error Rates Of The Kenward-Roger F-Test For A Split-Plot Design With Missing Values And Non-Normal Data, Miguel A. Padilla, Youngkyoung Min, Guili Zhang
Journal of Modern Applied Statistical Methods
The Type I error of the Kenward-Roger (KR) F-test was assessed through a simulation study for a between- by within-subjects split-plot design with non-normal ignorable missing data. The KR-test for the between- and within-subjects main effect was robust under all simulation variables investigated and when the data were missing completely at random (MCAR). This continued to hold for the between-subjects main effect when data were missing at random (MAR). For the interaction, the KR F-test performed fairly well at controlling Type I under MCAR and the simulation variables investigated. However, under MAR, the KR F-test for the …
Comparing Factor Loadings In Exploratory Factor Analysis: A New Randomization Test, W. Holmes Finch, Brian F. French
Comparing Factor Loadings In Exploratory Factor Analysis: A New Randomization Test, W. Holmes Finch, Brian F. French
Journal of Modern Applied Statistical Methods
Factorial invariance testing requires a referent loading to be constrained equal across groups. This study introduces a randomization test for comparing group exploratory factor analysis loadings so as to identify an invariant referent. Results show that it maintains the Type I error rate while providing adequate power under most conditions.
A Randomization Method To Control The Type I Error Rates In Best Subset Regression, Yasser A. Shehata, Paul White
A Randomization Method To Control The Type I Error Rates In Best Subset Regression, Yasser A. Shehata, Paul White
Journal of Modern Applied Statistical Methods
A randomization method for the assessment of statistical significance for best subsets regression is given. The procedure takes into account the number of potential predictors and the inter-dependence between predictors. The approach corrects a non-trivial problem with Type I errors and can be used to assess individual variable significance.
Correlation Between The Sample Mean And Sample Variance, Ramalingam Shanmugam
Correlation Between The Sample Mean And Sample Variance, Ramalingam Shanmugam
Journal of Modern Applied Statistical Methods
This article obtains a general formula to find the correlation coefficient between the sample mean and variance. Several particular results for major non-normal distributions are extracted to help students in classroom, clients during statistical consulting service.
Constructing Confidence Intervals For Spearman’S Rank Correlation With Ordinal Data: A Simulation Study Comparing Analytic And Bootstrap Methods, John Ruscio
Journal of Modern Applied Statistical Methods
Research shows good probability coverage using analytic confidence intervals (CIs) for Spearman’s rho with continuous data, but poorer coverage with ordinal data. A simulation study examining the latter case replicated prior results and revealed that coverage of bootstrap CIs was usually as good or better than coverage of analytic CIs.
Two Dimension Marginal Distributions Of Crossing Time And Renewal Numbers Related To Two-Stage Erlang Processes, Mir Ghulam Hyder Talpur, Iffat Zamir, M. Masoom Ali
Two Dimension Marginal Distributions Of Crossing Time And Renewal Numbers Related To Two-Stage Erlang Processes, Mir Ghulam Hyder Talpur, Iffat Zamir, M. Masoom Ali
Journal of Modern Applied Statistical Methods
The two dimensional marginal transform, probability density and cumulative probability distribution functions for the random variables TξN (time taken by servers during vacations), ξN (number of vacations taken by servers) and Nη (number of customers or units arriving in the system) are derived by taking combinations of these random variables. One random variable is controlled at one time to determine the effect of the other two random variables simultaneously.
Analyzing Incomplete Categorical Data: Revisiting Maximum Likelihood Estimation (Mle) Procedure, Hoo Ling Ping, M. Ataharul Islam
Analyzing Incomplete Categorical Data: Revisiting Maximum Likelihood Estimation (Mle) Procedure, Hoo Ling Ping, M. Ataharul Islam
Journal of Modern Applied Statistical Methods
Incomplete data poses formidable difficulties in the application of statistical techniques and requires special procedures to handle. The most common ways to solve this problem are by ignoring, truncating, censoring or collapsing those data, but these may lead to inappropriate conclusions because those data might contain important information. Most of the research for estimating cell probabilities involving incomplete categorical data is based on the EM algorithm. A likelihood approach is employed for estimating cell probabilities for missing values and makes comparisons between maximum likelihood estimation (MLE) and the EM algorithm. The MLE can provide almost the same estimates as that …
Size-Biased Generalized Negative Binomial Distribution, Khurshid Ahmad Mir
Size-Biased Generalized Negative Binomial Distribution, Khurshid Ahmad Mir
Journal of Modern Applied Statistical Methods
A size biased generalized negative binomial distribution (SBGNBD) is defined and a recurrence relationship for the moments of SBGNBD is established. The Bayes’ estimator for a parametric function of one parameter when two other parameters of a known size-biased generalized negative binomial distribution is derived. Prior information on one parameter is given by a beta distribution and the parameters in the prior distribution are assigned by computer using Monte Carlo and R-software.
Variance Estimation In Time Series Regression Models, Samir Safi
Variance Estimation In Time Series Regression Models, Samir Safi
Journal of Modern Applied Statistical Methods
The effect of variance estimation of regression coefficients when disturbances are serially correlated in time series regression models is studied. Variance estimation enters into confidence interval estimation, hypotheses testing, spectrum estimation, and expressions for the estimated standard error of prediction. Using computer simulations, the robustness of various estimators, including Estimated Generalized Least Squares (EGLS) was considered. The estimates of variance of the coefficient estimators produced by computer packages were considered. Models were generated with a second order auto-correlated error structure, considering the robustness of estimators based upon misspecified order. Ordinary Least Squares (OLS) (order zero) estimates outperformed first order EGLS. …
Bootstrap Confidence Intervals And Coverage Probabilities Of Regression Parameter Estimates Using Trimmed Elemental Estimation, Matthew Hall, Matthew S. Mayo
Bootstrap Confidence Intervals And Coverage Probabilities Of Regression Parameter Estimates Using Trimmed Elemental Estimation, Matthew Hall, Matthew S. Mayo
Journal of Modern Applied Statistical Methods
Mayo and Gray introduced the leverage residual-weighted elemental (LRWE) classification of regression estimators and a new method of estimation called trimmed elemental estimation (TEE), showing the efficiency and robustness of TEE point estimates. Using bootstrap methods, properties of various trimmed elemental estimator interval estimates to allow for inference are examined and estimates with ordinary least squares (OLS) and least sum of absolute values (LAV) are compared. Confidence intervals and coverage probabilities for the estimators using a variety of error distributions, sample sizes, and number of parameters are examined. To reduce computational intensity, randomly selecting elemental subsets to calculate the parameter …
Robust Predictive Inference For Multivariate Linear Models With Elliptically Contoured Distribution Using Bayesian, Classical And Structural Approaches, B. M. Golam Kibria
Robust Predictive Inference For Multivariate Linear Models With Elliptically Contoured Distribution Using Bayesian, Classical And Structural Approaches, B. M. Golam Kibria
Journal of Modern Applied Statistical Methods
Predictive distributions of future response and future regression matrices under multivariate elliptically contoured distributions are discussed. Under the elliptically contoured response assumptions, these are identical to those obtained under matric normal or matric-t errors using structural, Bayesian with improper prior, or classical approaches. This gives inference robustness with respect to departure from the reference case of independent sampling from the matric normal or matric t to multivariate elliptically contoured distributions. The importance of the predictive distribution for skewed elliptical models is indicated; the elliptically contoured distribution, as well as matric t distribution, have significant applications in statistical practices.
Delete And Revise Procedures For Two-Stage Short-Run Control Charts, Matthew E. Elam
Delete And Revise Procedures For Two-Stage Short-Run Control Charts, Matthew E. Elam
Journal of Modern Applied Statistical Methods
This article investigates the effect different delete and revise procedures have on the performance of twostage short-run control charting methodology in the second stage of its two stage procedure. Five variables control chart combinations, six delete and revise procedures, and various out-of-control situations in both stages are considered.
A Methodology To Improve Pci Use In Industry, Milind A. Phadnis, Matthew E. Elam
A Methodology To Improve Pci Use In Industry, Milind A. Phadnis, Matthew E. Elam
Journal of Modern Applied Statistical Methods
This article presents the development of a methodology using decision trees to resolve issues in industry with using process capability indices (PCIs). The methodology forms the structure of a prototype decision support system (PDSS) for PCI selection, calculation, and interpretation. Download instructions for the PDSS are available at http://program.20m.com.
Construction Of Insurance Scoring System Using Regression Models, Noriszura Ismail, Abdul Aziz Jemain
Construction Of Insurance Scoring System Using Regression Models, Noriszura Ismail, Abdul Aziz Jemain
Journal of Modern Applied Statistical Methods
This study suggests the regression models of Lognormal, Normal and Gamma for constructing insurance scoring system. The main advantage of a scoring system is that it can be used by insurers to differentiate between high and low risks insureds, thus allowing the profitability of insureds to be predicted.
The Multinomial Regression Modeling Of The Cause-Of-Death Mortality Of The Oldest Old In The U.S., Dudley L. Poston Jr., Hosik Min
The Multinomial Regression Modeling Of The Cause-Of-Death Mortality Of The Oldest Old In The U.S., Dudley L. Poston Jr., Hosik Min
Journal of Modern Applied Statistical Methods
The statistical modeling of the causes of death of the oldest old (persons aged 80 and over) in the U.S. in 2001 was conducted in this article. Data were analyzed using a multinomial logistic regression model (MNLM) because multiple causes of death are coded on death certificates and the codes are nominal. The percentage distribution of the 10 major causes of death among the oldest old was first examined; we next estimated a multinomial logistic regression equation to predict the likelihood of elders dying of one of the causes of death compared to dying of an “other cause.” The independent …
Frequency Domain Modeling With Piecewise Constant Spectra, Erhard Reschenhofer
Frequency Domain Modeling With Piecewise Constant Spectra, Erhard Reschenhofer
Journal of Modern Applied Statistical Methods
Using piecewise constant functions as models for the spectral density of the differenced log real U.S. GDP it was found that these models have the capacity to compete with the spectral densities implied by ARMA models. According to AIC and BIC the piecewise constant spectral densities are superior to ARMA.
Asymptotic Behavior Of Linearized Viscoelastic Flow Problem, Yinnian He, Yi Li
Asymptotic Behavior Of Linearized Viscoelastic Flow Problem, Yinnian He, Yi Li
Yi Li
In this article, we provide some asymptotic behaviors of linearized viscoelastic flows in a general two-dimensional domain with certain parameters small and the time variable large.
Asymptotic Behavior Of Linearized Viscoelastic Flow Problem, Yinnian He, Yi Li
Asymptotic Behavior Of Linearized Viscoelastic Flow Problem, Yinnian He, Yi Li
Mathematics and Statistics Faculty Publications
In this article, we provide some asymptotic behaviors of linearized viscoelastic flows in a general two-dimensional domain with certain parameters small and the time variable large.
Non-Parametric Quantile Selection For Extreme Distributions, Wan Zawiah Wan Zin, Abdul Aziz Jemain
Non-Parametric Quantile Selection For Extreme Distributions, Wan Zawiah Wan Zin, Abdul Aziz Jemain
Journal of Modern Applied Statistical Methods
The objective is to select the best non-parametric quantile estimation method for extreme distributions. This serves as a starting point for further research in quantile application such as in parameter estimation using LQ-moments method. Thirteen methods of non-parametric quantile estimation were applied on six types of extreme distributions and their efficiencies compared. Monte Carlo methods were used to generate the results, which showed that the method of Weighted Kernel estimator of Type 1 was more efficient than the other methods in many cases.
Multi-Group Confirmatory Factor Analysis For Testing Measurement Invariance In Mixed Item Format Data, Kim H. Koh, Bruno D. Zumbo
Multi-Group Confirmatory Factor Analysis For Testing Measurement Invariance In Mixed Item Format Data, Kim H. Koh, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
This simulation study investigated the empirical Type I error rates of using the maximum likelihood estimation method and Pearson covariance matrix for multi-group confirmatory factor analysis (MGCFA) of full and strong measurement invariance hypotheses with mixed item format data that are ordinal in nature. The results indicate that mixed item formats and sample size combinations do not result in inflated empirical Type I error rates for rejecting the true measurement invariance hypotheses. Therefore, although the common methods are in a sense sub-optimal, they don’t lead to researchers claiming that measures are functioning differently across groups – i.e., a lack of …
An Optimum Allocation With A Family Of Estimators Using Auxiliary Information In Sample Survey, Gajendra K. Vishwakarma, Housila P. Singh
An Optimum Allocation With A Family Of Estimators Using Auxiliary Information In Sample Survey, Gajendra K. Vishwakarma, Housila P. Singh
Journal of Modern Applied Statistical Methods
The problem of obtaining optimum allocation using auxiliary information in stratified random sampling. An optimum allocation with a family of estimators is obtained and its efficiency is compared with that of Neyman allocation based on Srivastava (1971) class of estimators and the optimum allocation suggested by Zaidi et al., (1989). It is shown that the proposed allocation is better in the sense having smaller variance compared to other optimum allocation.
Adaptive Estimation Of Heteroscedastic Linear Regression Model Using Probability Weighted Moments, Faqir Muhammad, Muhammad Aslam, G.R. Pasha
Adaptive Estimation Of Heteroscedastic Linear Regression Model Using Probability Weighted Moments, Faqir Muhammad, Muhammad Aslam, G.R. Pasha
Journal of Modern Applied Statistical Methods
An adaptive estimator is presented by using probability weighted moments as weights rather than conventional estimates of variances for unknown heteroscedastic errors while estimating a heteroscedastic linear regression model. Empirical studies of the data generated by simulations for normal, uniform, and logistically distributed error terms support our proposed estimator to be quite efficient, especially for small samples.
Least Squares Percentage Regression, Chris Tofallis
Least Squares Percentage Regression, Chris Tofallis
Journal of Modern Applied Statistical Methods
In prediction, the percentage error is often felt to be more meaningful than the absolute error. We therefore extend the method of least squares to deal with percentage errors, for both simple and multiple regression. Exact expressions are derived for the coefficients, and we show how such models can be estimated using standard software. When the relative error is normally distributed, least squares percentage regression is shown to provide maximum likelihood estimates. The multiplicative error model is linked to least squares percentage regression in the same way that the standard additive error model is linked to ordinary least squares regression.
On Some Properties Of Quasi-Negative-Binomial Distribution And Its Applications, Anwar Hassan, Sheikh Bilal
On Some Properties Of Quasi-Negative-Binomial Distribution And Its Applications, Anwar Hassan, Sheikh Bilal
Journal of Modern Applied Statistical Methods
The quasi-negative-binomial distribution was applied to queuing theory for determining the distribution of total number of customers served before the queue vanishes under certain assumptions. Some structural properties (probability generating function, convolution, mode and recurrence relation) for the moments of quasi-negative-binomial distribution are discussed. The distribution’s characterization and its relation with other distributions were investigated. A computer program was developed using R to obtain ML estimates and the distribution was fitted to some observed sets of data to test its goodness of fit.
Topological Dynamics Of Two-Piece Eventually Expanding Maps, Youngna Choi
Topological Dynamics Of Two-Piece Eventually Expanding Maps, Youngna Choi
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
In this work we show that two-piece eventually expanding maps have the same topological dynamics as two-piece expanding maps. A two-piece eventually expanding map possesses an invariant set that is either a topological attractor or can be perturbed to become one.
Analyzing The Effects Of Coupons And Promotion In The Grocery Retail Sector, Milena Hanna Chotard
Analyzing The Effects Of Coupons And Promotion In The Grocery Retail Sector, Milena Hanna Chotard
Masters Theses
Modern scanner technology is pervasive throughout the retailing sector of the economy and is almost universal in the food retail industry. Along with loyalty programs, it has led to the development of massive databases which accurately and proficiently track the purchasing habits of customers. Making use of this information is one of the most important efforts in the management of this sector to further increase profitability.
This thesis explores the application of several statistical techniques to extract specific information from two large databases of customer purchasing behavior at a major US grocery chain. In particular, we first focus on the …