Statistics and Probability Commons^™

Design & Analysis Of A Computer Experiment For An Aerospace Conformance Simulation Study, Ryan W. Gryder

Theses and Dissertations

Within NASA's Air Traffic Management Technology Demonstration # 1 (ATD-1), Interval Management (IM) is a flight deck tool that enables pilots to achieve or maintain a precise in-trail spacing behind a target aircraft. Previous research has shown that violations of aircraft spacing requirements can occur between an IM aircraft and its surrounding non-IM aircraft when it is following a target on a separate route. This research focused on the experimental design and analysis of a deterministic computer simulation which models our airspace configuration of interest. Using an original space-filling design and Gaussian process modeling, we found that aircraft delay assignments …

Generating Random Vectors Using Transformation With Multiple Roots And Its Applications, Qidi Peng, Henry Schellhorn, Lu Zhu

Applications and Applied Mathematics: An International Journal (AAM)

An approach is proposed to generate random vectors using transformation with multiple roots. This approach generalizes the one-dimensional inverse transformation with multiple roots method to higher dimensions, i.e., to random vectors with or without densities. In this approach, multiple roots of the transformation and probabilities of selecting each of the roots are derived. The strategies for constructing such a transformation are discussed and several examples are presented to motivate this simulation approach.

Spss Programs For Addressing Two Forms Of Power For Multiple Regression Coefficients, Christopher Aberson

Journal of Modern Applied Statistical Methods

This paper presents power analysis tools for multiple regression. The first takes input of correlations between variables and sample size and outputs power for multiple predictors. The second addresses power to detect significant effects for all of the predictors in the model. Both employ user-friendly SPSS Custom Dialogs.

Global Network Inference From Ego Network Samples: Testing A Simulation Approach, Jeffrey A. Smith

Department of Sociology: Faculty Publications

Network sampling poses a radical idea: that it is possible to measure global network structure without the full population coverage assumed in most network studies. Network sampling is only useful, however, if a researcher can produce accurate global network estimates. This article explores the practicality of making network inference, focusing on the approach introduced in Smith (2012). The method uses sampled ego network data and simulation techniques to make inference about the global features of the true, unknown network. The validity check here includes more difficult scenarios than previous tests, including those that go beyond the initial scope conditions of …

Considerations For Screening Designs And Follow-Up Experimentation, Robert D. Leonard

Theses and Dissertations

The success of screening experiments hinges on the effect sparsity assumption, which states that only a few of the factorial effects of interest actually have an impact on the system being investigated. The development of a screening methodology to harness this assumption requires careful consideration of the strengths and weaknesses of a proposed experimental design in addition to the ability of an analysis procedure to properly detect the major influences on the response. However, for the most part, screening designs and their complementing analysis procedures have been proposed separately in the literature without clear consideration of their ability to perform …

A Semiparametric Estimation For Regression Functions In The Partially Linear Autoregressive Time Series Model, R. Farnoosh, M. Hajebi, S. J. Mortazavi

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, a semiparametric method is proposed for estimating regression function in the partially linear autoregressive time series model . Here, we consider a combination of parametric forms and nonlinear functions, in which the errors are independent. Semiparametric and nonparametric curve estimation provides a useful tool for exploring and understanding the structure of a nonlinear time series data set to make for a more efficient study in the partially linear autoregressive model. The unknown parameters are estimated using the conditional nonlinear least squares method, and the nonparametric adjustment is also estimated by defining and minimizing the local L2 -fitting …

Some General Guidelines For Choosing Missing Data Handling Methods In Educational Research, Jehanzeb R. Cheema

Journal of Modern Applied Statistical Methods

The effect of a number of factors, such as the choice of analytical method, the handling method for missing data, sample size, and proportion of missing data, were examined to evaluate the effect of missing data treatment on accuracy of estimation. A methodological approach involving simulated data was adopted. One outcome of the statistical analyses undertaken in this study is the formulation of easy-to-implement guidelines for educational researchers that allows one to choose one of the following factors when all others are given: sample size, proportion of missing data in the sample, method of analysis, and missing data handling method.

Ridge Regression And Ill-Conditioning, Ghadban Khalaf, Mohamed Iguernane

Journal of Modern Applied Statistical Methods

Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary Least Squares (OLS) estimator in the presence of multicollinearity. This article proposes new methods for estimating the ridge parameter in case of ordinary ridge regression. A simulation study evaluates the performance of the proposed estimators based on the Mean Squared Error (MSE) criterion and indicates that, under certain conditions, the proposed estimators perform well compared to the OLS estimator and another well-known estimator reviewed.

Double Bootstrap Confidence Interval Estimates With Censored And Truncated Data, Jayanthi Arasan, Mohd B. Adam

Journal of Modern Applied Statistical Methods

Traditional inferential procedures often fail with censored and truncated data, especially when sample sizes are small. In this paper we evaluate the performances of the double and single bootstrap interval estimates by comparing the double percentile (DB-p), double percentile-t (DB-t), single percentile (B-p), and percentile-t (B-t) bootstrap interval estimation methods via a coverage probability study when the data is censored using the log logistic model. We then apply the double bootstrap intervals to real right censored lifetime data on 32 women with breast cancer and failure data on 98 brake pads where all the observations were left truncated.

Quantitative Evidence For The Use Of Simulation And Randomization In The Introductory Statistics Course, Nathan L. Tintle, Ally Rogers, Beth Chance, George Cobb, Allan Rossman, Soma Roy, Todd Swanson, Jill Vanderstoep

Faculty Work Comprehensive List

The use of simulation and randomization in the introductory statistics course is gaining popularity, but what evidence is there that these approaches are improving students’ conceptual understanding and attitudes as we hope? In this talk I will discuss evidence from early full-length versions of such a curriculum, covering issues such as (a) items and scales showing improved conceptual performance compared to traditional curriculum, (b) transferability of findings to different institutions, (c) retention of conceptual understanding post-course and (d) student attitudes. Along the way I will discuss a few areas in which students in both simulation/randomization courses and the traditional course …

Simulating Influenza Transmission With Network Data, Henry V. Bongiovi

Statistics

Simulating Influenza Transmission with Real Network Data

Henry Bongiovi BS Statistics, California Polytechnic State University, San Luis Obispo

[email protected]

Keywords: Network Data, Simulation, Education, Influenza, Epidemic

Disease has been humanities arch rival since the dawn of our existence. As such, we have been trying our best to understand its spread and proliferation. One of the most common diseases, Influenza, is also one of the most complex. To understand the complexities of its spread would greatly improve our ability to combat it and other diseases like it. Using R in conjunction with the package statnet, I have created a simulation of …

Bias And Precision Of The Squared Canonical Correlation Coefficient Under Nonnormal Data Condition, Lesley F. Leach, Robin K. Henson

Journal of Modern Applied Statistical Methods

Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated with the squared canonical correlation coefficient (R_c²). The majority of R_c² estimates were found to be extremely biased, but the magnitude of bias was impacted little by the degree of nonnormality.

Comparison Of Different Methods For Estimating Log-Normal Means, Qi Tang

Electronic Theses and Dissertations

The log-normal distribution is a popular model in many areas, especially in biostatistics and survival analysis where the data tend to be right skewed. In our research, a total of ten different estimators of log-normal means are compared theoretically. Simulations are done using different values of parameters and sample size. As a result of comparison, ``A degree of freedom adjusted" maximum likelihood estimator and Bayesian estimator under quadratic loss are the best when using the mean square error (MSE) as a criterion. The ten estimators are applied to a real dataset, an environmental study from Naval Construction Battalion Center (NCBC), …

Exponentially Weighted Moving Average Charts For Monitoring The Process Generalized Variance, Anna Khamitova

College of Graduate Studies: Theses & Dissertations

The exponentially weighted moving average chart based on the sample generalized variance is studied under the independent multivariate normal model for the vector of quality measurements. The performance of the chart is based on an analysis of the chart's initial and steady-state run length distributions. The three methods that are commonly used to determinate run length distribution, simulation, the integral equation method, and the Markov chain approximation are discussed. The integral equation and Markov chain approaches are analytical methods that require a nu- merical method for determining the probability density and cumulative distribution functions describing the distribution of the sample …

Robust Regression Methods For Massively Decayed Intelligence Data, Akiva Joachim Lorenz

Wayne State University Dissertations

Homeland Security, sponsored by governmental initiatives, has become a vibrant academic research field. However, most efforts were placed with the recognition of threats (e.g. theory) and response options. Less effort was placed in the analysis of the collected data through statistical modeling. In a field that collects more than 20 terabyte of information per minute though diverse overt and covert means and indexes it for future research, understanding how different statistical models behave when it comes to massively decayed data is of vital importance.

Using Monte Carlo methods, three regression techniques (ordinary least squares, least-trimmed, and maximum likelihood) were tested …

Testing The Population Coefficient Of Variation, Shipra Banik, B. M. Golam Kibria, Dinesh Sharma

Journal of Modern Applied Statistical Methods

The coefficient of variation (CV), which is used in many scientific areas, measures the variability of a population relative to its mean and standard deviation. Several methods exist for testing the population CV. This article compares a proposed bootstrap method to existing methods. A simulation study was conducted under both symmetric and skewed distributions to compare the performance of test statistics with respect to empirical size and power. Results indicate that some of the proposed methods are useful and can be recommended to practitioners.

Statistical Inferences For Lomax Distribution Based On Record Values (Bayesian And Classical), Parviz Nasiri, Saman Hosseini

Journal of Modern Applied Statistical Methods

A maximum likelihood estimation (MLE) based on records is obtained and a proper prior distribution to attain a Bayes estimation (both informative and non-informative) based on records for quadratic loss and squared error loss functions is also calculated. The study considers the shortest confidence interval and Highest Posterior Distribution confidence interval based on records, and using Mean Square Error MSE criteria for point estimation and length criteria for interval estimation, their appropriateness to each other is examined.

Retention Of Statistical Concepts In A Preliminary Randomization-Based Introductory Statistics Curriculum, Nathan L. Tintle, Kylie Topliff, Jill Vanderstoep, Vicki-Lynn Holmes, Todd Swanson

Faculty Work Comprehensive List

Previous research suggests that a randomization-based introductory statistics course may improve student learning compared to the consensus curriculum. However, it is unclear whether these gains are retained by students post-course. We compared the conceptual understanding of a cohort of students who took a randomization-based curriculum (n = 76) to a cohort of students who used the consensus curriculum (n = 79). Overall, students taking the randomization-based curriculum showed higher conceptual retention in areas emphasized in the curriculum, with no significant decrease in conceptual retention in other areas. This study provides additional support for the use of randomization-methods in teaching introductory …

Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison

Statistics

As a student, I noticed that the statistical package R (http://www.r-project.org) would have several benefits of its usage in the classroom. One benefit to the package is its free and open-source nature. This would be a great benefit for instructors and students alike since it would be of no cost to use, unlike other statistical packages. Due to this, students could continue using the program after their statistical courses and into their professional careers. It would be good to expose students while they are in school to a tool that professionals use in industry. R also has powerful …

The Quotient Of The Beta-Weibull Distribution, Nonhle Channon Mdziniso

Theses, Dissertations and Capstones

A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are, the beta-Normal (Eugene et al. [15]); beta-Gumbel (Nadarajah and Kotz [18]); beta-Exponential (Nadarajah and Kotz [19]); beta-Weibull (Famoye et al. [6]); beta-Rayleigh (Akinsete and Lowe [3]); beta-Laplace (Kozubowshi and Nadarajah [20]); and beta-Pareto (Akinsete et al. [4]), among a few others. Many useful statistical properties arising from these distributions and their applications to real life data have been discussed in literature. One approach by which a new statistical distribution is generated is by the transformation of random variables having known …

Parsing The Relationship Between Baserunning And Batting Abilities Within Lineups, Ben S. Baumer, James Piette, Brad Null

Statistical and Data Sciences: Faculty Publications

A baseball team's offensive prowess is a function of two types of abilities: batting and baserunning. While each has been studied extensively in isolation, the effects of their interaction is not well understood. We model offensive output as a scalar function f of an individual player's batting and baserunning profile z. Each of these profiles is in turn estimated from Retrosheet data using heirarchical Bayesian models. We then use the SimulOutCome simulation engine as a method to generate values of f(z) over a fine grid of points. Finally, for each of several methods of taking the extra base, we graphically …

A Framework For Generating Data To Simulate Application Scoring, Kenneth Kennedy, Sarah Jane Delany, Brian Mac Namee

Conference papers

In this paper we propose a framework to generate artificial data that can be used to simulate credit risk scenarios. Artificial data is useful in the credit scoring domain for two reasons. Firstly, the use of artificial data allows for the introduction and control of variability that can realistically be expected to occur, but has yet to materialise in practice. The ability to control parameters allows for a thorough exploration of the performance of classification models under different conditions. Secondly, due to non-disclosure agreements and commercial sensitivities, obtaining real credit scoring data is a problematic and time consuming task. By …

Empirical Comparison Of Some Test Statistics For Testing The Mean Of A Poisson Distribution, B. M. Golam Kibria, Florence George

Applications and Applied Mathematics: An International Journal (AAM)

This paper considers the problem of hypotheses testing of the mean of a Poisson distribution. Accordingly we consider the following test statistics: Wald, WCC, Score (S), FT, VS, RVS, Exact and Bayes test statistics. A simulation study based on both one and two sided alternatives has been conducted to compare the performances of the test statistics. The study suggests that for a large sample size, all proposed test statistics except VCC and FT perform well in the sense of correct type I error rate of the test and power. However, for a small sample size, Score and VS have better …

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

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.

Statistical Properties Of A Convoluted Beta-Weibull Distribution, Jianan Sun

Theses, Dissertations and Capstones

A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are the beta-normal (Eugene et.al. (2002)); beta-Gumbel (Nadarajah and Kotz (2004)); beta-exponential (Nadarajah and Kotz (2006)); beta-Weibull (Famoye et al. (2005)); beta-Rayleigh (Akinsete and Lowe (2008)); beta-Laplace (Kozubowski and Nadarajah (2008)); and beta-Pareto (Akinsete et al. (2008)), among a few others. Many useful statistical properties arising from these distributions and their applications to real life data have been discussed in the literature. One approach by which a new statistical distribution is generated is by the transformation of random variables having known …

Meta-Analysis Of Single-Case Data: A Monte Carlo Investigation Of A Three Level Model, Corina M. Owens

USF Tampa Graduate Theses and Dissertations

Numerous ways to meta-analyze single-case data have been proposed in the literature, however, consensus on the most appropriate method has not been reached. One method that has been proposed involves multilevel modeling. This study used Monte Carlo methods to examine the appropriateness of Van den Noortgate and Onghena's (2008) raw data multilevel modeling approach to the meta-analysis of single-case data. Specifically, the study examined the fixed effects (i.e., the overall average baseline level and the overall average treatment effect) and the variance components (e.g., the between person within study variance in the average baseline level, the between study variance in …

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 …

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.

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.