Statistical Models Commons^™

The Influence Of The Electric Supply Industry On Economic Growth In Less Developed Countries, Edward Richard Bee

Dissertations

This study measures the impact that electrical outages have on manufacturing production in 135 less developed countries using stochastic frontier analysis and data from World Bank’s Investment Climate surveys. Outages of electricity, for firms with and without backup power sources, are the most frequently cited constraint on manufacturing growth in these surveys.

Outages are shown to reduce output below the production frontier by almost five percent in Africa and by a lower percentage in South Asia, Southeast Asia and the Middle East and North Africa. Production response to outages is quadratic in form. Outages also increase labor cost, reduce exports …

Multilevel Models For Longitudinal Data, Aastha Khatiwada

Electronic Theses and Dissertations

Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of fitting individual models for each …

Newsvendor Models With Monte Carlo Sampling, Ijeoma W. Ekwegh

Electronic Theses and Dissertations

Newsvendor Models with Monte Carlo Sampling by Ijeoma Winifred Ekwegh The newsvendor model is used in solving inventory problems in which demand is random. In this thesis, we will focus on a method of using Monte Carlo sampling to estimate the order quantity that will either maximizes revenue or minimizes cost given that demand is uncertain. Given data, the Monte Carlo approach will be used in sampling data over scenarios and also estimating the probability density function. A bootstrapping process yields an empirical distribution for the order quantity that will maximize the expected profit. Finally, this method will be used …

The Influence Of Model Resolution On The Simulated Sensitivity Of North Atlantic Tropical Cyclone Maximum Intensity To Sea Surface Temperature, Sarah Strazzo, James Elsner, Timothy Larow, Hiroyuki Murakami, Michael Wehner, Ming Zhao

Publications

No abstract provided.

Analysis Off Dependent Discrete Choices Using Gaussian Copula, Arjun Poddar

Mathematics & Statistics Theses & Dissertations

A popular tool for analyzing product choices of consumers is the well-known conditional logit discrete choice model. Originally publicized by McFadden (1974), this model assumes that the random components of the underlying latent utility functions of the consumers follow independent Gumbel distributions. However, in practice the independence assumption may be violated and a more reasonable model should account for the dependence of the utilities. In this dissertation we use the Gaussian copula with compound symmetric and autoregressive of order one correlation matrices to construct a general multivariate model for the joint distribution of the utilities. The induced correlations on the …

Bayesian Nonparametric Approaches To Multiple Testing, Density Estimation, And Supervised Learning, William Cipolli Iii

Theses and Dissertations

This dissertation presents methods for several applications of Polya tree models. These novel nonparametric approaches to the problems of multiple testing, density estimation and supervised learning provide an alternative to other parametric and nonparametric models. In Chapter 2, the proposed approximate finite Polya tree multiple testing procedure is very successful in correctly classifying the observations with non-zero mean in a computationally efficient manner; this holds even when the non-zero means are simulated from a mean-zero distribution. Further, the model is capable of this for “interestingly different” observations in the cases where that is of interest. Chapter 3 proposes discrete, and …

Well I'Ll Be Damned - Insights Into Predictive Value Of Pedigree Information In Horse Racing, Timothy Baker Mr, Ming-Chien Sung, Johnnie Johnson Professor, Tiejun Ma

International Conference on Gambling & Risk Taking

Fundamental form characteristics like how fast a horse ran at its last start, are widely used to help predict the outcome of horse racing events. The exception being in races where horses haven’t previously competed, such as Maiden races, where there is little or no publicly available past performance information. In these types of events bettors need only consider a simplified suite of factors however this is offset by a higher level of uncertainty. This paper examines the inherent information content embedded within a horse’s ancestry and the extent to which this information is discounted in the United Kingdom bookmaker …

Quantifying Transit Access In New York City: Formulating An Accessibility Index For Analyzing Spatial And Social Patterns Of Public Transportation, Maxwell S. Siegel

Theses and Dissertations

This paper aims to analyze accessibility within New York City’s transportation system through creating unique accessibility indices. Indices are detailed and implemented using GIS, analyzing the distribution of transit need and access. Regression analyses are performed highlighting relationships between demographics and accessibility and recommendations for transit expansion are presented.

Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman

LSU New Orleans Theses and Dissertations

Sea state is a subjective quantity whose accuracy depends on an observer’s ability to translate local wind waves into numerical scales. It provides an analytical tool for estimating the impact of the sea on data quality and operational safety. Tasks dependent on the characteristics of local sea surface conditions often require accurate and immediate assessment. An attempt to automate sea state classification using eleven years of ship motion and sea state observation data is made using parametric modeling of distribution-based confidence and tolerance intervals and a probabilistic model using sea state frequencies. Models utilizing distribution intervals are not able to …

Construction Of Pair-Wise Balanced Design, Rajarathinam Arunachalam, Mahalakshmi Sivasubramanian, Dilip Kumar Ghosh

Journal of Modern Applied Statistical Methods

A new procedure for construction of pair wise balanced design with equal replication and un-equal block sizes based on factorial design have been evolved. Numerical illustration also provided. It was found that the constructed pair wise balanced design was found to be universal optimal.

Takens Theorem With Singular Spectrum Analysis Applied To Noisy Time Series, Thomas K. Torku

Electronic Theses and Dissertations

The evolution of big data has led to financial time series becoming increasingly complex, noisy, non-stationary and nonlinear. Takens theorem can be used to analyze and forecast nonlinear time series, but even small amounts of noise can hopelessly corrupt a Takens approach. In contrast, Singular Spectrum Analysis is an excellent tool for both forecasting and noise reduction. Fortunately, it is possible to combine the Takens approach with Singular Spectrum analysis (SSA), and in fact, estimation of key parameters in Takens theorem is performed with Singular Spectrum Analysis. In this thesis, we combine the denoising abilities of SSA with the Takens …

Integration Of Multi-Platform High-Dimensional Omic Data, Xuebei An

Dissertations and Theses (Open Access)

The development of high-throughput biotechnologies have made data accessible from different platforms, including RNA sequencing, copy number variation, DNA methylation, protein lysate arrays, etc. The high-dimensional omic data derived from different technological platforms have been extensively used to facilitate comprehensive understanding of disease mechanisms and to determine personalized health treatments. Although vital to the progress of clinical research, the high dimensional multi-platform data impose new challenges for data analysis. Numerous studies have been proposed to integrate multi-platform omic data; however, few have efficiently and simultaneously addressed the problems that arise from high dimensionality and complex correlations.

In my dissertation, I …

Analysis And Modeling Of U.S. Army Recruiting Markets, Joshua L. Mcdonald

Theses and Dissertations

The United States Army Recruiting Command (USAREC) is charged with finding, engaging, and ultimately enlisting young Americans for service as Soldiers in the U.S. Army. USAREC must decide how to allocate monthly enlistment goals, by aptitude and education level, across its 38 subordinate recruiting battalions in order to maximize the number of enlistment contracts produced each year. In our research, we model the production of enlistment contracts as a function of recruiting supply and demand factors which vary over the recruiting battalion areas of responsibility. Using county-level data for the period of recruiting year RY2010 through RY2013 mapped to recruiting …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Binomial Regression With A Misclassified Covariate And Outcome, Sheng Luo, Wenyaw Chan, Michelle A Detry, Paul J Massman, R S. Doody

Faculty, Staff and Students Publications

Misclassification occurring in either outcome variables or categorical covariates or both is a common issue in medical science. It leads to biased results and distorted disease-exposure relationships. Moreover, it is often of clinical interest to obtain the estimates of sensitivity and specificity of some diagnostic methods even when neither gold standard nor prior knowledge about the parameters exists. We present a novel Bayesian approach in binomial regression when both the outcome variable and one binary covariate are subject to misclassification. Extensive simulation results under various scenarios and a real clinical example are given to illustrate the proposed approach. This approach …

Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret

UW Biostatistics Working Paper Series

We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …

Spatiotemporal Meta-Analysis: Reviewing Health Psychology Phenomena Over Space And Time., Blair T. Johnson

CHIP Documents

This supplemental material is meant to support this article:

Johnson, B. T., Crowley, E., & Marrouch, N. Spatiotemporal meta-analysis: Reviewing health psychology phenomena over space and time. Health Psychology Review.

Specifically, it is a database of GDPs per capita for nations in the world between 1800 and 2015. It is archived here to support an online supplement to this article.

GDP per capita

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 …

Collective Action And Decision Making: An Analysis Of Economic Modeling And Environmental Free-Riding, Thomas Miller 16

Honor Scholar Theses

No abstract provided.

Development In Normal Mixture And Mixture Of Experts Modeling, Meng Qi

Theses and Dissertations--Statistics

In this dissertation, first we consider the problem of testing homogeneity and order in a contaminated normal model, when the data is correlated under some known covariance structure. To address this problem, we developed a moment based homogeneity and order test, and design weights for test statistics to increase power for homogeneity test. We applied our test to microarray about Down’s syndrome. This dissertation also studies a singular Bayesian information criterion (sBIC) for a bivariate hierarchical mixture model with varying weights, and develops a new data dependent information criterion (sFLIC).We apply our model and criteria to birth- weight and gestational …