Applied Statistics Commons^™

Statistical Partition Problem For Exponential Populations And Statistical Surveillance Of Cancers In Louisiana, Jin Gu

LSU New Orleans Theses and Dissertations

In this dissertation, we consider the problem of partitioning a set of

k population with respect

to a control population. For this problem some multistage methodologies are proposed and their

properties are derived. Using the Monte Carlo simulation techniques, the small and moderate

sample size performance of the proposed procedure are studied.

We have also considered at statistical surveillance of various cancers in Louisiana.

Analyzing Alcohol Behavior In San Luis Obispo, Ariana Montes

Statistics

No abstract provided.

Viewing The Moon In Infrared, Kyle Beekman

Statistics

Man has been fascinated by the heavens since ancient times, yet there is still so much that we don’t know. This project was created by Dr. Gary Hughes with goal of obtaining information about the moon and other objects in the vicinity of the Earth. The project was mostly experimental in nature and there was no specific goal at the outset of the project. In the end the project focused on the moon and meteors that traveled through the Earth’s upper atmosphere. Throughout the month of August, students traveled to the Mount Barcroft Research Station in the Eastern Sierras to …

A Vegetation Analysis On Horn Island, Mississippi, Ca. 1940 Using Characteristic Dimensions Derived From Historical Aerial Photography, Guy Wilburn Jeter Jr.

Master's Theses

Horn Island is part of the MS/AL barrier island chain in the northern Gulf of Mexico located approximately 18kn off the coast of Mississippi. This island’s habitats have undergone many transitions over the last several decades. The goal of this study was to quantify habitat change over a seventy year period using historical black and white photography from 1940. Using present NAIP imagery from the USDA, habitat structure was estimated by using geo-statistics, and second order statistics, from a co-occurrence matrix, to characterize texture for habitat classification. Percent land cover was then calculated to determine overall land cover change over …

Security Analysis On Network Systems Based On Some Stochastic Models, Xiaohu Li

LSU New Orleans Theses and Dissertations

Due to great effort from mathematicians, physicists and computer scientists, network science has attained rapid development during the past decades. However, because of the complexity, most researches in this area are conducted only based upon experiments and simulations, it is critical to do research based on theoretical results so as to gain more insight on how the structure of a network affects the security. This dissertation introduces some stochastic and statistical models on certain networks and uses a k-out-of-n tolerant structure to characterize both logically and physically the behavior of nodes. Based upon these models, we draw several illuminating results …

Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, W. Coleman Conley

Undergraduate Economic Review

Over the last twenty-five years, minor league baseball franchises have defined firm mobility. Revisiting the work of Michael C. Davis (2006), I construct a logistic regression model to predict which cities house minor league baseball teams. Six variables are tested for inclusion in the model, including population, income level, the number of major-league professional sports teams in a city, five-year population change, and distance from the closest professional team. Based on the model's predicted probabilities, cities are ranked in order of highest probability of having a team at each of the different levels from Class A to Class AAA.

Retained-Components Factor Transformation: Factor Loadings And Factor Score Predictors In The Column Space Of Retained Components, André Beauducel, Frank Spohn

Journal of Modern Applied Statistical Methods

Factor loadings optimally account for the non-diagonal elements of the covariance matrix of observed variables. Principal component analysis leads to components accounting for a maximum of the variance of the observed variables. Retained-components factor transformation is proposed in order to combine the advantages of factor analysis and principal component analysis.

Pairwise Comparison In Repeated Measures, I.C.A. Oyeka, C. C. Nnanatu

Journal of Modern Applied Statistical Methods

Sometimes a random sample of subjects or patients may be exposed to a battery of diagnostic tests or medication over time and interest is on determining whether there is progressive remission of condition, disease or symptom. Also perhaps early in a program or experiment, subjects or candidates may be required to significantly improve in their performance rates at the current trial relative to an immediately preceding trial, otherwise they may have to withdraw from or drop out. The research interest would then be to determine some critical minimum marginal success rate to guide the management in decision making as well …

A Comparison Of Methods For Group Prediction With High Dimensional Data, Holmes Finch

Journal of Modern Applied Statistical Methods

High dimensional data is the situation in which the number of variables included in an analysis approaches or exceeds the sample size. In the context of group classification, researchers are typically interested in finding a model that can be used to correctly place an individual into their appropriate group; e.g. correctly diagnose individuals with depression. However, when the size of the training sample is small and the number of predictors used to differentiate the groups is larger, standard approaches such as discriminant analysis may not work well. In order to address this issue, statisticians have developed a number of tools …

Objective Priors For Estimation Of Extended Exponential Geometric Distribution, Pedro L. Ramos, Fernando A. Moala, Jorge A. Achcar

Journal of Modern Applied Statistical Methods

A Bayesian analysis was developed with different noninformative prior distributions such as Jeffreys, Maximal Data Information, and Reference. The aim was to investigate the effects of each prior distribution on the posterior estimates of the parameters of the extended exponential geometric distribution, based on simulated data and a real application.

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.

Bayesian Inference For Volatility Of Stock Prices, Juliet G. D'Cunha, K. A. Rao

Journal of Modern Applied Statistical Methods

Lognormal distribution is widely used in the analysis of failure time data and stock prices. Maximum likelihood and Bayes estimator of the coefficient of variation of lognormal distribution along with confidence/credible intervals are developed. The utility of Bayes procedure is illustrated by analyzing prices of selected stocks.

Local Bandwidths For Improving Performance Statistics Of Model-Robust Regression 2, Efosa Edionwe, Julian L. Mbegbu

Journal of Modern Applied Statistical Methods

Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.

Contrast Of Bayesian And Classical Sample Size Determination, Farhana Sadia, Syed S. Hossain

Journal of Modern Applied Statistical Methods

Sample size determination is a prerequisite for statistical surveys. A comprehensive overview of the Bayesian approach for computation of the sample size, and a comparison with classical approaches, is presented. Two surveys are taken as example to illustrate the accuracy and efficiency of each approach, and to make recommendations about which method is preferred. The Bayesian approach of sample size determination may require fewer subjects if proper prior information is available.

The Information Criterion, Masume Ghahramani

Journal of Modern Applied Statistical Methods

The Akaike information criterion, AIC, is widely used for model selection. Using the AIC as the estimator of asymptotic unbias for the second term Kullbake-Leibler risk considers the divergence between the true model and offered models. However, it is an inconsistent estimator. A proposed approach the problem is the use of A'IC, a consistently offered information criterion. Model selection of classic and linear models are considered by a Monte Carlo simulation.

Gumbel-Weibull Distribution: Properties And Applications, Raid Al-Aqtash, Carl Lee, Felix Famoye

Journal of Modern Applied Statistical Methods

Some properties of the Gumbel-Weibull distribution including the mean deviations and modes are studied. A detailed discussion of regions of unimodality and bimodality is given. The method of maximum likelihood is proposed for estimating the distribution parameters and a simulation is conducted to study the performance of the method. Three tests are given for testing the significance of a distribution parameter. The applications of Gumbel-Weibull distribution are emphasized. Five data sets are used to illustrate the flexibility of the distribution in fitting unimodal and bimodal data sets.

Fitting Stereotype Logistic Regression Models For Ordinal Response Variables In Educational Research (Stata), Xing Liu

Journal of Modern Applied Statistical Methods

The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not have the procedure developed to directly estimate the model. The purpose of this article was to illustrate the stereotype logistic (SL) regression model, and apply it to estimate mathematics proficiency level of high school students using Stata. In addition, it compared …

Optimal Location Design For Prediction Of Spatial Correlated Environmental Functional Data, Mahdi Rasekhi, B. Jamshidi, F. Rivaz

Journal of Modern Applied Statistical Methods

The optimal choice of sites to make spatial prediction is critical for a better understanding of really spatio-temporal data. It is important to obtain the essential spatio-temporal variability of the process in determining optimal design, because these data tend to exhibit both spatial and temporal variability. Two new methods of prediction for spatially correlated functional data are considered. The first method models spatial dependency by fitting variogram to empirical variogram, similar to ordinary kriging (univariate approach). The second method models spatial dependency by linear model co-regionalization (multivariate approach). The variance of prediction method was chosen as the optimization design criterion. …

Missing Data And The Statistical Modeling Of Adolescent Pregnancy, Dudley L. Poston Dr., Eugenia Conde Dr.

Journal of Modern Applied Statistical Methods

Missing data is a pervasive problem in social science research. Many techniques have been developed to handle the problem. Different ways of handling missing data were shown to lead to different results in statistical models. A demonstration was given based on statistical modeling of the likelihood of a woman reporting having had an adolescent pregnancy by handling missing data with several different approaches. Results indicate that many of the independent variables in the model vary in whether they are, or are not, statistically significant in predicting the log odds of a woman having a teen pregnancy, and in the ranking …

Conover’S F Test As An Alternative To Durbin’S Test, Donald J. Best, John Charles Rayner

Journal of Modern Applied Statistical Methods

Data consisting of ranks within blocks are considered for balanced incomplete block designs. An F test statistic from ANOVA is better approximated by an F distribution than the Durbin statistic is approximated by a chi-squared distribution. Indicative powers demonstrate that the F test is generally superior to Durbin’s test.

A Bivariate Distribution With Conditional Gamma And Its Multivariate Form, Sumen Sen, Rajan Lamichhane, Norou Diawara

Journal of Modern Applied Statistical Methods

A bivariate distribution whose marginal are gamma and beta prime distribution is introduced. The distribution is derived and the generation of such bivariate sample is shown. Extension of the results are given in the multivariate case under a joint independent component analysis method. Simulated applications are given and they show consistency of our approach. Estimation procedures for the bivariate case are provided.

Reliability Estimates Of Generalized Poisson Distribution And Generalized Geometric Series Distribution, Adil H. Khan, T R. Jan

Journal of Modern Applied Statistical Methods

Discrete distributions have played an important role in the reliability theory. In order to obtain Bayes estimators, researchers have adopted various conventional techniques. Generalizing the results of Maiti (1995), Chaturvadi and Tomer (2002) dealt with the problem of estimating P{X₁, X₂, …, X_k ≤ Y}, where random variables X and Y were assumed to follow a negative binomial distribution. Agit et al. obtained Bayesian estimates of the reliability functions and P{X₁, X₂, …, X_k ≤ Y} considering X and Y following binomial and Poisson …

Comparison Of Individual And Moving Range Chart Combinations To Individual Charts In Terms Of Arl After Designing For A Common “All Ok” Arl, Dewi Rahardja

Journal of Modern Applied Statistical Methods

In some process monitoring situations, consecutive measurements are spaced widely apart in time, making monitoring process aim and spread difficult. This study uses three cases to compare the effectiveness of two such monitoring schemes, i.e., the X chart alone (X-only chart) and the Individuals and Moving Range Chart Combination (X/MR chars), in terms of Average Run Length (ARL) after designing for a common “all OK” (in-control) ARL. The study finds that X chart alone is sufficient (and hence, recommended) in detecting changes in all the 3 cases: changes in the process mean, changes in the process standard deviation, and changes …

Front Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

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Improved Randomization Tests For A Class Of Single-Case Intervention Designs, Joel R. Levin, John M. Ferron, Boris S. Gafurov

Journal of Modern Applied Statistical Methods

Forty years ago, Eugene Edgington developed a single-case AB intervention design-and-analysis procedure based on a random determination of the point at which the B phase would start. In the present simulation studies encompassing a variety of AB-type contexts, it is demonstrated that by also randomizing the order in which the A and B phases are administered, a researcher can markedly increase the procedure’s statistical power.

Robust Winsorized Shrinkage Estimators For Linear Regression Model, Nileshkumar H. Jadhav, D N. Kashid

Journal of Modern Applied Statistical Methods

In multiple linear regression, the ordinary least squares estimator is very sensitive to the presence of multicollinearity and outliers in the response variable. To handle these problems in the data, Winsorized shrinkage estimators are proposed and the performance of these estimators is evaluated through mean square error sense.

Discrete Generalized Burr-Type Xii Distribution, B. A. Para, T. R. Jan

Journal of Modern Applied Statistical Methods

A discrete analogue of generalized Burr-type XII distribution is introduced using a general approach of discretizing a continuous distribution. It may be worth exploring the possibility of developing a discrete version of the six parameter generalized Burr-type XII distribution for use in modeling a discrete data. This distribution is suggested as a suitable reliability model to fit a range of discrete lifetime data, as it is shown that hazard rate function can attain monotonic increasing (deceasing) shape for certain values of parameters. The equivalence of discrete generalized Burr-type XII (DGBD-XII) and continuous generalized Burr-type XII (GBD-XII) distributions has been established. …

Bayesian Estimation Of The Parameters Of Two-Component Mixture Of Rayleigh Distribution Under Doubly Censoring, Tahassum N. Sindhu, Navid Feroze, Muhammad Aslam

Journal of Modern Applied Statistical Methods

Recently, the Bayesian analysis of the two-component mixture of lifetime models under singly type I censored samples was discussed. The Bayes estimation of the parameters of mixture of two Rayleigh distributions (MTRD) is developed under doubly censoring. Different informative priors, under squared error loss function and k-loss function, have been assumed for the posterior estimation. The performance of different estimators has been compared in terms of posterior risks by analyzing the simulated and real life data sets.

Survival Estimation Using Bootstrap, Jackknife And K-Repeated Jackknife Methods, Johnson A. Adewara, Ugochukwu A. Mbata

Journal of Modern Applied Statistical Methods

Three re-sampling techniques are used to estimate the survival probabilities from an exponential life-time distribution. The aim is to employ a technique to obtain a parameter estimate for a two-parameter exponential distribution. The re-sampling methods considered are: Bootstrap estimation method (BE), Jackknife estimation method (JE) and the k-repeated Jackknife estimation method (KJE). The methods were computed to obtain the mean square error (MSE) and mean percentage error (MPE) based on simulated data. The estimates of the two-parameter exponential distribution were substituted to estimate survival probabilities. Results show that the MSE value is reduced when the K–repeated jackknife method …

Some Methods Of Estimation From Censored Samples In Exponential And Gamma Models, R R. L Kantam, B Sriram

Journal of Modern Applied Statistical Methods

Two popular life testing models exponential and one where its generalization is gamma are considered. Estimation of scale parameter from a general Type-II doubly censored sample is attempted by the principle of maximum likelihood method. Resulting equations found to be giving iterative solutions. As an alternative to iterative solution certain admissible modifications to the estimating equations are suggested in special cases. The resulting estimates are compared with the exact maximum likelihood estimates analytically or through simulation. The results are also extended for reliability estimation.