Statistics and Probability Commons^™

A Simulation Study Of The Relative Efficiency Of The Minimized Integrated Square Error Estimator (L2e) For Phase I Control Charting, John N. Dyer

Journal of Modern Applied Statistical Methods

Parameter estimates used in control charting, the sample mean and variance, are based on maximum likelihood estimation (MLE). Unfortunately, MLEs are not robust to contaminated data and can lead to improper conclusions regarding parameter values. This article proposes a more robust estimation technique; the minimized integrated square error estimator (L2E).

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.

Logistic Regression Models For Higher Order Transition Probabilities Of Markov Chain For Analyzing The Occurrences Of Daily Rainfall Data, Narayan Chanra Sinha, M. Ataharul Islam, Kazi Saleh Ahamed

Journal of Modern Applied Statistical Methods

Logistic regression models for transition probabilities of higher order Markov models are developed for the sequence of chain dependent repeated observations. To identify the significance of these models and their parameters a test procedure for a likelihood ratio criterion is developed. A method of model selection is suggested on the basis of AIC and BIC procedures. The proposed models and test procedures are applied to analyze the occurrences of daily rainfall data for selected stations in Bangladesh. Based on results from these models, the transition probabilities of first order Markov model for temperature and humidity provided the most suitable option …

Number Of Replications Required In Monte Carlo Simulation Studies: A Synthesis Of Four Studies, Daniel J. Mundform, Jay Schaffer, Myoung-Jin Kim, Dale Shaw, Ampai Thongteeraparp, Pornsin Supawan

Journal of Modern Applied Statistical Methods

Monte Carlo simulations are used extensively to study the performance of statistical tests and control charts. Researchers have used various numbers of replications, but rarely provide justification for their choice. Currently, no empirically-based recommendations regarding the required number of replications exist. Twenty-two studies were re-analyzed to determine empirically-based recommendations.

Matched-Pair Studies With Misclassified Ordinal Data, Tze-San Lee

Journal of Modern Applied Statistical Methods

The problem of matched-pair studies with misclassified ordinal data is considered. Misclassification is assumed to occur only between the adjacent columns/rows. Bias-adjusted generalized odds ratio and a test for marginal homogeneity are presented to account for misclassification bias. Data from lambing records of 227 Merino ewes are used to illustrate how to calculate these bias-adjusted estimators and – because validation data are not available – a sensitivity analysis is conducted.

A Robust Root Mean Square Standardized Effect Size In One-Way Fixed-Effects Anova, Guili Zhang, James Algina

Journal of Modern Applied Statistical Methods

A robust Root Mean Square Standardized Effect Size (RMSSER) was developed to address the unsatisfactory performance of the Root Mean Square Standardized Effect Size. The coverage performances of the confidence intervals (CI) for RMSSE_R were investigated. The coverage probabilities of the non-central F distribution-based CI for RMSSER were adequate.

The Overall F-Tests For Seasonal Unit Roots Under Nonstationary Alternatives: Some Theoretical Results And A Monte Carlo Investigation, Ghassen El Montasser

Journal of Modern Applied Statistical Methods

In many empirical studies concerning seasonal time series, it has been shown that the whole set of unit roots associated with seasonal random walks are not present. This article focuses on the overall F-tests for seasonal unit roots under some nonstationary alternatives different from the seasonal random walk. The asymptotic theory of these tests is established for these cases using a new approach based on circulant matrix concepts. The simulation results joined to this theoretic analysis showed that the overall F-tests, as well as their augmented versions, maintained high power against the nonstationary alternatives.

Weighting Large Datasets With Complex Sampling Designs: Choosing The Appropriate Variance Estimation Method, Sara Mann, James Chowhan

Journal of Modern Applied Statistical Methods

Using the Canadian Workplace and Employee Survey (WES), three variance estimation methods for weighting large datasets with complex sampling designs are compared: simple final weighting, standard bootstrapping and mean bootstrapping. Using a logit analysis, it is shown - depending on which weighting method is used - different predictor variables are significant. The potential lack of independence inherent in a multi-stage cluster sample design, as in the WES, results in a downward bias in the variance when conducting statistical inference (using the simple final weight), which in turn results in increased Type I errors. Bootstrap methods can account for the survey’s …

Using Finite Mixture Modeling To Deal With Systematic Measurement Error: A Case Study, Min Liu, Gregory R. Hancock, Jeffrey R. Harring

Journal of Modern Applied Statistical Methods

Conventional methods and analyses view measurement error as random. A scenario is presented where a variable was measured with systematic error. Mixture models with systematic parameter constraints were used to test hypotheses in the context of general linear models; this accommodated the heterogeneity arising due to systematic measurement error.

Estimating Internal Consistency Using Bayesian Methods, Miguel A. Padilla, Guili Zhang

Journal of Modern Applied Statistical Methods

Bayesian internal consistency and its Bayesian credible interval (BCI) are developed and Bayesian internal consistency and its percentile and normal theory based BCIs were investigated in a simulation study. Results indicate that the Bayesian internal consistency is relatively unbiased under all investigated conditions and the percentile based BCIs yielded better coverage performance.

An Analysis Of The Relationship Between Economic Development And Demographic Characteristics In The United States, Chad M. Heyne

HIM 1990-2015

Over the past several decades there has been extensive research done in an attempt to determine what demographic characteristics affect economic growth, measured in GDP per capita. Understanding what influences the growth of a country will vastly help policy makers enact policies to lead the country in a positive direction. This research focuses on isolating a new variable, women in the work force. As well as isolating a new variable, this research will modify a preexisting variable that was shown to be significant in order to make the variable more robust and sensitive to recessions. The intent of this thesis …

Martingale Couplings And Bounds On Tails Of Probability Distributions, Kyle Luh

HMC Senior Theses

Wassily Hoeffding, in his 1963 paper, introduces a procedure to derive inequalities between distributions. This method relies on finding a martingale coupling between the two random variables. I have developed a construction that establishes such couplings in various urn models. I use this construction to prove the inequality between the hypergeometric and binomial random variables that appears in Hoeffding's paper. I have then used and extended my urn construction to create new inequalities.

The Geozoic Supereon, M. Kowalewski, J. L. Payne, F. A. Smith, Steve C. Wang, D. W. Mcshea, S. Xiao, P. M. Novack-Gottshall, C. R. Mcclain, R. A. Krause, A. G. Boyer, S. Finnegan, S. K. Lyons, J. A. Stempien, J. Alroy, P. A. Spaeth

Mathematics & Statistics Faculty Works

No abstract provided.

Factors That Inhibit Or Enhance Maternal Coping With Stillbirth In Chhattisgarh, India, Lisa R. Roberts

Loma Linda University Electronic Theses, Dissertations & Projects

Background: Over half of the known stillbirths occur in four highly populated countries—India among them. While acknowledged as a significant public health issue in western societies, little is known about maternal coping with stillbirth in developing countries. The purpose of this mixed methods study is to explore how issues of gender and power, social support, coping efforts, and religious beliefs influence perinatal grief outcomes among poor women in rural Chhattisgarh, India.

Methods: In Phase 1 of this mixed methods study, grounded theory methods were used to explore perceptions regarding stillbirth. A de-identified medical records review of 536 deliveries at Christian …

A Comparison Of Spatial Prediction Techniques Using Both Hard And Soft Data, Megan L. Liedtke Tesar

Department of Statistics: Dissertations, Theses, and Student Research

The overall goal of this research, which is common to most spatial studies, is to predict a value of interest at an unsampled location based on measured values at nearby sampled locations.  To accomplish this goal, ordinary kriging can be used to obtain the best linear unbiased predictor.  However, there is often a large amount of variability surrounding the measurements of environmental variables, and traditional prediction methods, such as ordinary kriging, do not account for an attribute with more than one level of uncertainty.  This dissertation addresses this limitation by introducing a new methodology called weighted kriging.  This prediction technique …

A Stochastic Model For Wind Turbine Power Quality Using A Levy Index Analysis Of Wind Velocity Data, Jonathan Blackledge, Eugene Coyle, Derek Kearney

Conference papers

The power quality of a wind turbine is determined by many factors but time-dependent variation in the wind velocity are arguably the most important. After a brief review of the statistics of typical wind speed data, a non- Gaussian model for the wind velocity is introduced that is based on a Levy distribution. It is shown how this distribution can be used to derive a stochastic fractional diusion equation for the wind velocity as a function of time whose solution is characterised by the Levy index. A Levy index numerical analysis is then performed on wind velocity data for both …

Local Likelihood In Regression Analysis Of Proportional Mean Residual Life Model With Censored Survival Data, Yang Ni

All Theses

As a function of time t, mean residual life (MRL) is the remaining life expectancy of a subject given its survival to t. In survival analysis, the relationship between a survival time and a covariate can be conveniently modeled with the proportionality mean residual life (MRL) model proposed by Oakes and Dasu(1990) and provides an alternative to the Cox proportionality hazards model, Cox (1972). In this paper we consider the proportional MRL regression model with a nonparametric covariate effect. We discuss estimation of the proportional function when the baseline MRL function is not specified. We develop the asymptotic properties of …

Climate Change And Community Dynamics: A Hierarchical Bayesian Model Of Resource-Driven Changes In A Desert Rodent Community, Glenda M. Yenni

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Predicting effects of climate change on species persistence often assumes that those species are responding to abiotic effects alone. However, biotic interactions between community members may affect species’ ability to respond to abiotic changes. Latent Gaussian models of resource availability using precipitation and NDVI and accounting for spatial autocorrelation and rodent group-level uncertainty in the process are developed to detect differences in seasons, groups, and the experimental removal of one group. Precipitation and NDVI have overall positive effects on rodent energy use as expected, but meaningful differences were detected. Differences in the importance of seasonality when the dominant group was …

Estimation Of Beta In A Simple Functional Capital Asset Pricing Model For High Frequency Us Stock Data, Yan Zhang

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

This project applies the methods of functional data analysis (FDA) to intra-daily returns of US corporations. It focuses on an extension of the Capital Asset Pricing Model (CAPM) to such returns. The CAPM is essentially a linear regression with the slope coefficient β. Returns of an asset are regressed on index return. We compare the estimates of β obtained for the daily and intra-daily returns. The variability of these estimates is assessed by two bootstrap methods. All computations are performed using statistical software R. Customized functions are developed to process the raw data, estimate the parameters and assess their variability. …

Controlling Error Rates With Multiple Positively-Dependent Tests, Abdullah Al Masud

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

It is a typical feature of high dimensional data analysis, for example a microarray study, that a researcher allows thousands of statistical tests at a time. All inferences for the tests are determined using the p-values; a smaller p-value than the α-level of the test signifies a statistically significant test. As the number of tests increases, the chance of observing some small p-values is very high even when all null hypotheses are true. Consequently, we make wrong conclusions on the hypotheses. This type of potential problem frequently happens when we test several hypotheses simultaneously, i.e., the multiple testing problem. …

Nonparametric Methods In Varying Coefficient Models And Quantile Regression Models, Chinthaka Kuruwita

All Dissertations

This dissertation aims to address two problems in nonparametric regression models. An estimation issue in generalized varying coefficient models and a hypothesis testing issue in nonparametric quantile regression models is discussed.
We propose a new estimation method for generalized varying coefficient models where the link function is specified up to some smoothness conditions. Consistency and asymptotic normality of the estimated varying coefficient functions are established. Simulation results and a real data application demonstrate the usefulness of the new method.
A new approach for testing the equality of nonparametric quantile regression functions is also presented. Based on marked empirical processes, we …

Examining Child Sexual Abuse And Future Parenting: An Application Of Latent Class Modeling, Kimberly W. D'Zatko

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This study was designed to empirically derive latent classes of mothers who were sexually abused during childhood and to assess the association between depression, alcohol/drug use, supportive intimate partner, and specific classes.

One hundred six women between the ages of 20 and 44 years (M = 27) who reported having been sexually abused during childhood (CSA) and 158 non-CSA mothers between the ages of 20 and 43 years (M = 23) were interviewed and assessed along six parenting dimensions. Logistic regression models evaluated the association between psychoemotional variables and specific classes.

The final model consisted of three classes—53.2%, …

Statistical Inference Of A Measure For Two Binomial Variates, Serena Petersen

UNLV Theses, Dissertations, Professional Papers, and Capstones

We study measures of a comparison for two independent binomial variates which frequently occur in real situations. An estimator for measure of reduction (MOR) is considered for two sample proportions based on a modified maximum likelihood estimation. We study the desirable properties of the estimator: the asymptotic behavior of its unbiasedness and the variance of the estimator. Since the measure ρ is approximately normally distributed when sample sizes are sufficiently large, one may establish approximate confidence intervals for the true value of the estimators. For numerical study, the Monte Carlo experiment is carried out for the various scenarios of two …

Implementation Of Numerically Stable Hidden Markov Model, Usha Ramya Tatavarty

UNLV Theses, Dissertations, Professional Papers, and Capstones

A Hidden Markov model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (hidden) states. HMM is an extremely flexible tool and has been successfully applied to a wide variety of stochastic modeling tasks. One of the first applications of HMM is speech recognition. Later they came to be known for their applicability in handwriting recognition, part-of-speech tagging and bio-informatics.

In this thesis, we will explain the mathematics involved in HMMs and how to efficiently perform HMM computations using dynamic programming (DP) which makes it easy to implement …

Calcium Supplemental Usage And Potential Health Issues Sssociated With The Rate Of Usage In Las Vegas, Nv, Tanesha Nicole Moss

UNLV Theses, Dissertations, Professional Papers, and Capstones

Calcium is a very important nutrient and as such, it is very important that all humans consume sufficient amounts. However, some calcium supplements have been known to contain small quantities of lead. This research project used a retrospective approach to explore the trade-off between the benefits of calcium vs. the potential lead exposure amongst people who are taking these supplements. A survey consisting of 10 questions was used to try to assess the rate of consumption of specific types of calcium supplements. This research project obtained lead levels in calcium supplements from previous research and applied that data into this …

Arima Models For Bank Failures: Prediction And Comparison, Fangjin Cui

UNLV Theses, Dissertations, Professional Papers, and Capstones

The number of bank failures has increased dramatically over the last twenty-two years. A common notion in economics is that some banks can become "too big to fail." Is this still a true statement? What is the relationship, if any, between bank sizes and bank failures? In this thesis, the proposed modeling techniques are applied to real bank failure data from the FDIC. In particular, quarterly data from 1989:Q1 to 2010:Q4 are used in the data analysis, which includes three major parts: 1) pairwise bank failure rate comparisons using the conditional test (Przyborowski and Wilenski, 1940); 2) development of the …

Modeling Mortality Rates For Leukemia Between Men And Women In The United States, Blessed Quansah

UNLV Theses, Dissertations, Professional Papers, and Capstones

Leukemia related deaths increased dramatically over the last forty years. Leukemia is a malignant disease or cancer of the bone marrow and blood. It is characterized by the uncontrolled accumulation of blood cells. Leukemia is divided into two categories: myelogenous or lymphocytic, each of which can be acute or chronic. The terms, myelogenous or lymphocytic denote the cell type involved.

In this thesis, the proposed modeling techniques are applied to leukemia deaths data from the Surveillance Epidemiology and End Results (SEER). In particular, annual deaths data from 1969 to 2007 are used in the data analysis, which includes three major …

Effects Of Inlet Conditions On Diffuser Outlet Performance, Zaccary A. Poots

UNLV Theses, Dissertations, Professional Papers, and Capstones

Building air distribution terminal system designers and system installers require accurate quantitative information on the performance of the installed system to achieve optimum efficiency and levels of human comfort. This requires field installation adjustment values from published ideal pressure loss, air distribution and sound generation installation performance. This study documents the air output performance of different installation configurations of six types of ceiling diffusers and compares the results to performance when installed according to ANSI/ASHRAE Standard 70-2006. A diffuser inlet supply plenum was designed for optimum flow and used to acquire a baseline set of data covering the six types …

A Statistical Model For Long-Term Forecasting Of Strong Sand Dust Storms, Siqi Tan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Dust elevated into the atmosphere by dust storms has numerous environmental consequences. These include contributing to climate change; modifying local weather conditions; producing chemical and biological changes in the oceans; and affecting soil formation, surface water, groundwater quality, crop growth, and survival (Goudie and Middleton, 1992). Societal impacts include disruptions to air, road and rail traffic; interruption of radio services; the myriad effects of static-electricity generation; property damage; and health effects on humans and animals (Warner, 2004).

In this thesis, we extend the idea of empirical recurrence rate (ERR), developed by Ho (2008), to model the temporal trend of the …

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 4: Predictive Analysis - Regression Modeling, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.