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Articles 31 - 52 of 52
Full-Text Articles in Physical Sciences and Mathematics
Bayesian Threshold Moving Average Models, Mahmoud M. Smadi, M. T. Alodat
Bayesian Threshold Moving Average Models, Mahmoud M. Smadi, M. T. Alodat
Journal of Modern Applied Statistical Methods
A Bayesian approach in threshold moving average model for time series with two regimes is provided. The posterior distribution of the delay and threshold parameters are used to examine and investigate the intrinsic characteristics of this nonlinear time series model. The proposed approach is applied to both simulated data and a real data set obtained from a chemical system. Key words: Threshold time series, moving average model, Bayesian
Maximum Likelihood Solution For The Linear Structural Relationship With Three Parameters Known, Androulla Michaeloudis
Maximum Likelihood Solution For The Linear Structural Relationship With Three Parameters Known, Androulla Michaeloudis
Journal of Modern Applied Statistical Methods
A maximum likelihood solution is obtained for the simple linear structural relation model where the underlying incidental distribution and one error variance are assumed known. Expressions for the asymptotic standard errors of the maximum likelihood estimates are obtained and these are verified using a simulation study.
Estimating The Non-Existent Mean And Variance Of The F-Distribution By Simulation, Hamid Reza Kamali, Parisa Shahnazari-Shahrezaei
Estimating The Non-Existent Mean And Variance Of The F-Distribution By Simulation, Hamid Reza Kamali, Parisa Shahnazari-Shahrezaei
Journal of Modern Applied Statistical Methods
In theory, all moments of some probability distributions do not necessarily exist. In the other words, they may be infinite or undefined. One of these distributions is the F-distribution whose mean and variance have not been defined for the second degree of freedom less than 3 and 5, respectively. In some cases, a large statistical population having an F-distribution may exist and the aim is to obtain its mean and variance which are an estimation of the non-existent mean and variance of F-distribution. This article considers a large sample F-distribution to estimate its non-existent mean and variance using Simul8 simulation …
On Simulating Univariate And Multivariate Burr Type Iii And Type Xii Distributions, Todd C. Headrick, Mohan D. Pant, Yanyan Sheng
On Simulating Univariate And Multivariate Burr Type Iii And Type Xii Distributions, Todd C. Headrick, Mohan D. Pant, Yanyan Sheng
Mohan Dev Pant
This paper describes a method for simulating univariate and multivariate Burr Type III and Type XII distributions with specified correlation matrices. The methodology is based on the derivation of the parametric forms of a pdf and cdf for this family of distributions. The paper shows how shape parameters can be computed for specified values of skew and kurtosis. It is also demonstrated how to compute percentage points and other measures of central tendency such as the mode, median, and trimmed mean. Examples are provided to demonstrate how this Burr family can be used in the context of distribution fitting using …
Creation Of Synthetic Discrete Response Regression Models, Joseph Hilbe
Creation Of Synthetic Discrete Response Regression Models, Joseph Hilbe
Joseph M Hilbe
The development and use of synthetic regression models has proven to assist statisticians in better understanding bias in data, as well as how to best interpret various statistics associated with a modeling situation. In this article I present code that can be easily amended for the creation of synthetic binomial, count, and categorical response models. Parameters may be assigned to any number of predictors (which are shown as continuous, binary, or categorical), negative binomial heterogeneity parameters may be assigned, and the number of levels or cut points and values may be specified for ordered and unordered categorical response models. I …
Assessing Trends: Monte Carlo Trials With Four Different Regression Methods, Daniel R. Thompson
Assessing Trends: Monte Carlo Trials With Four Different Regression Methods, Daniel R. Thompson
Journal of Modern Applied Statistical Methods
Ordinary Least Squares (OLS), Poisson, Negative Binomial, and Quasi-Poisson Regression methods were assessed for testing the statistical significance of a trend by performing 10,000 simulations. The Poisson method should be used when data follow a Poisson distribution. The other methods should be used when data follow a normal distribution.
Application Of The Truncated Skew Laplace Probability Distribution In Maintenance System, Gokarna R. Aryal, Chris P. Tsokos
Application Of The Truncated Skew Laplace Probability Distribution In Maintenance System, Gokarna R. Aryal, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
A random variable X is said to have the skew-Laplace probability distribution if its pdf is given by f(x) = 2g(x)G(λx), where g (.) and G (.), respectively, denote the pdf and the cdf of the Laplace distribution. When the skew Laplace distribution is truncated on the left at 0 it is called it the truncated skew Laplace (TSL) distribution. This article provides a comparison of TSL distribution with twoparameter gamma model and the hypoexponential model, and an application of the subject model in maintenance system is studied.
Least Absolute Value Vs. Least Squares Estimation And Inference Procedures In Regression Models With Asymmetric Error Distributions, Terry E. Dielman
Least Absolute Value Vs. Least Squares Estimation And Inference Procedures In Regression Models With Asymmetric Error Distributions, Terry E. Dielman
Journal of Modern Applied Statistical Methods
A Monte Carlo simulation is used to compare estimation and inference procedures in least absolute value (LAV) and least squares (LS) regression models with asymmetric error distributions. Mean square errors (MSE) of coefficient estimates are used to assess the relative efficiency of the estimators. Hypothesis tests for coefficients are compared on the basis of empirical level of significance and power.
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.
Jmasm16: Pseudo-Random Number Generation In R For Some Univariate Distributions, Hakan Demirtas
Jmasm16: Pseudo-Random Number Generation In R For Some Univariate Distributions, Hakan Demirtas
Journal of Modern Applied Statistical Methods
An increasing number of practitioners and applied researchers started using the R programming system in recent years for their computing and data analysis needs. As far as pseudo-random number generation is concerned, the built-in generator in R does not contain some important univariate distributions. In this article, complementary R routines that could potentially be useful for simulation and computation purposes are provided.
Pseudo-Random Number Generation In R For Commonly Used Multivariate Distributions, Hakan Demirtas
Pseudo-Random Number Generation In R For Commonly Used Multivariate Distributions, Hakan Demirtas
Journal of Modern Applied Statistical Methods
An increasing number of practitioners and applied statisticians have started using the R programming system in recent years for their computing and data analysis needs. As far as pseudo-random number generation is concerned, the built-in generator in R does not contain multivariate distributions. In this article, R routines for widely used multivariate distributions are presented.
A Comparison Of Geostatistical And Spatial Autoregressive Approaches For Dealing With Spatially Correlated Residuals In Regression Analysis For Precision Agriculture Applications, Ignacio Colonna, Matías Ruffo, Germán Bollero, Don Bullock
A Comparison Of Geostatistical And Spatial Autoregressive Approaches For Dealing With Spatially Correlated Residuals In Regression Analysis For Precision Agriculture Applications, Ignacio Colonna, Matías Ruffo, Germán Bollero, Don Bullock
Conference on Applied Statistics in Agriculture
Regressions such as Grain yield=f(soil,landscape) are frequently reported in precision agriculture research, and are typically computed using conventional OLS methods, implicitly ignoring spatial correlation of the residuals. This oversight can have a marked effect on the final conclusions derived from these regressions. A further issue is, which approach should be used to account for this problem? We investigated this question using a 2 year data set that includes sitespecific soil and topographic information and soybean yields and compare regression results from direct covariance representation and spatial autoregressive approaches. Our results show that the coefficients from both spatial approaches are in …
You Think You’Ve Got Trivials?, Shlomo S. Sawilowsky
You Think You’Ve Got Trivials?, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Effect sizes are important for power analysis and meta-analysis. This has led to a debate on reporting effect sizes for studies that are not statistically significant. Contrary and supportive evidence has been offered on the basis of Monte Carlo methods. In this article, clarifications are given regarding what should be simulated to determine the possible effects of piecemeal publishing trivial effect sizes.
Not All Effects Are Created Equal: A Rejoinder To Sawilowsky, J. Kyle Roberts, Robin K. Henson
Not All Effects Are Created Equal: A Rejoinder To Sawilowsky, J. Kyle Roberts, Robin K. Henson
Journal of Modern Applied Statistical Methods
In the continuing debate over the use and utility of effect sizes, more discussion often helps to both clarify and syncretize methodological views. Here, further defense is given of Roberts & Henson (2002) in terms of measuring bias in Cohen’s d, and a rejoinder to Sawilowsky (2003) is presented.
A Simulation Study Of Exponential Semiv Arlo Gram Estimation, Edward E. Gbur, Bruce A. Craig, Hao Zhang
A Simulation Study Of Exponential Semiv Arlo Gram Estimation, Edward E. Gbur, Bruce A. Craig, Hao Zhang
Conference on Applied Statistics in Agriculture
Incorporating the spatial structure of data from agricultural field experiments into inference procedures has become an important topic in recent years. As part of a larger project to determine whether or not reliable predictions and estimates can be obtained for sample sizes often encountered in traditional field experimentation, this paper focuses on the small sample estimation of the parameters of the exponential semivariogram model. Simulation studies were conducted for both expanding and fixed domains. The results indicate large sample to sample variation in sample and fitted semivariograms, neither of which may be "close" to the true model. Distributions of individual …
A Simulation Study Of The Impact Of Forecast Recovery For Control Charts Applied To Arma Processes, John N. Dyer, B. Michael Adams, Michael D. Conerly
A Simulation Study Of The Impact Of Forecast Recovery For Control Charts Applied To Arma Processes, John N. Dyer, B. Michael Adams, Michael D. Conerly
Journal of Modern Applied Statistical Methods
Forecast-based schemes are often used to monitor autocorrelated processes, but the resulting forecast recovery has a significant effect on the performance of control charts. This article describes forecast recovery for autocorrelated processes, and the resulting simulation study is used to explain the performance of control charts applied to forecast errors.
Jmasm3: A Method For Simulating Systems Of Correlated Binary Data, Todd C. Headrick
Jmasm3: A Method For Simulating Systems Of Correlated Binary Data, Todd C. Headrick
Journal of Modern Applied Statistical Methods
An efficient algorithm is derived for generating systems of correlated binary data. The procedure allows for the specification of all pairwise correlations within each system. Intercorrelations between systems can be specified qualitatively. The procedure requires the simultaneous solution of a system of equations for obtaining the threshold probabilities to generate each system of binary data. A numerical example is provided to demonstrate that the procedure generates correlated binary variables that yield correlations in close agreement with the specified population correlations.
Optimum Preventive Maintenance Policies For The Amraam Missile, Scott J. Ruflin
Optimum Preventive Maintenance Policies For The Amraam Missile, Scott J. Ruflin
Theses and Dissertations
The overall objective of this research effort was to formulate a preventive maintenance strategy for AMRAAM missiles subject to extended captive carry flight time. A preventive maintenance policy is only applicable if the item in question is aging, or deteriorating with time. Therefore, a supporting objective of this research is to characterize the aging process of the missile system through a non-parametric analysis of its Mean Residual Life (MRL) function. Three non-parametric, censored-data MRL function estimation techniques discussed in the literature are examined via a numerical example. All three estimation techniques provide MRL functions that exhibit greatly exaggerated decreasing trends …
Empirical Estimates Of Power For Binomial Data With Mixed Models, R. K. Splan, L. D. Van Vleck, H. D. Hafs
Empirical Estimates Of Power For Binomial Data With Mixed Models, R. K. Splan, L. D. Van Vleck, H. D. Hafs
Conference on Applied Statistics in Agriculture
Observations on return to estrus from anestrus postpartum beef cows were used as the basis for a simulation study to develop a method to determine numbers of locations and animals per treatment per location to achieve a specified power of test. Estimates of among location and total variance were obtained by REML from the data set and then used to generate simulated data for the binomial trait. Each combination of several pre-determined factors was replicated 1000 times. Pre-determined factors were number of locations, number of animals per treatment per location, desired detectable difference due to treatment, alpha-probability level and ratio …
Nepotism In Honey Bees, Computer Programs And Scientific Hypotheses, Benjamin P. Oldroyd, Thomas E. Rinderer
Nepotism In Honey Bees, Computer Programs And Scientific Hypotheses, Benjamin P. Oldroyd, Thomas E. Rinderer
Conference on Applied Statistics in Agriculture
Page et al. (1989) attempted to show that bees on queen cells preferentially reared their super sisters as replacement queens rather than half sisters. In support of their contention, they used computer simulation to model the biological system. We argue that the simulation did not accurately reflect the biological system in several important respects. We show that random data will produce the same kinds of statistical significance as the actual data.
Monte Carlo Simulation Of The Game Of Twenty-One, Douglas E. Loer
Monte Carlo Simulation Of The Game Of Twenty-One, Douglas E. Loer
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
The purpose of this paper is to demonstrate the application of computer simulation to the game of Twenty-One to predict a player's expected return from the game. Twenty-One has traditionally been one of the most popular casino games and has attracted much effort to accurately estimate the house's true advantage. Probability theory has been tried, but the thousands of different combinations of cards possible in all hands throughout the entire pack make it practically impossible to apply probability theory without overlooking some possibilities. For this reason, Twenty-One is a perfect candidate for simulation. By blocking several simulations, normal theory can …
The Practical Solutions And Computer Program Of Two Statistical Problems In Simulation, Yee Fong
The Practical Solutions And Computer Program Of Two Statistical Problems In Simulation, Yee Fong
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
In the last several years monte-carlo simulation has become a major tool for the analysis of complex queuing systems which are no readily amenable to analysis by conventional mathematical methods. By a complex queueing system is mean a system composed of, physically or by analogy, a network of stations or servers with traffic units moving through all or some of the servers, into the system and out or around within the system. A traffic unit desiring service by a server may either have to enter a queue first or may be served immediately. Such systems have been simulated often with …