Open Access. Powered by Scholars. Published by Universities.®

Statistical Models Commons

Open Access. Powered by Scholars. Published by Universities.®

2018

Electronic Theses and Dissertations

Discipline
Institution
Keyword

Articles 1 - 8 of 8

Full-Text Articles in Statistical Models

Effectiveness Of Prescribed Fire On Meeting Fuel Load And Wildlife Habitat Management Objectives In East Texas National Forests, Trey Wall Dec 2018

Effectiveness Of Prescribed Fire On Meeting Fuel Load And Wildlife Habitat Management Objectives In East Texas National Forests, Trey Wall

Electronic Theses and Dissertations

Using standardized methodology outlined by the United States Forest Service and the National Forests and Grasslands in Texas’ Fire Monitoring Program for data collection, the efficacy of current Forest Service prescribed burn regimes were analyzed for 24 study sites in East Texas National Forests. Study sites were located within Sam Houston, Davy Crockett, and Angelina/Sabine National Forests. Efficacy was determined by comparing defined management objectives established by the Forest Service to the data collected at the study sites. The results conclude that most objectives, as outlined by the Forest Service, are not being met with the current practices. Re-visitation of …


Wald Confidence Intervals For A Single Poisson Parameter And Binomial Misclassification Parameter When The Data Is Subject To Misclassification, Nishantha Janith Chandrasena Poddiwala Hewage Aug 2018

Wald Confidence Intervals For A Single Poisson Parameter And Binomial Misclassification Parameter When The Data Is Subject To Misclassification, Nishantha Janith Chandrasena Poddiwala Hewage

Electronic Theses and Dissertations

This thesis is based on a Poisson model that uses both error-free data and error-prone data subject to misclassification in the form of false-negative and false-positive counts. We present maximum likelihood estimators (MLEs), Fisher's Information, and Wald statistics for Poisson rate parameter and the two misclassification parameters. Next, we invert the Wald statistics to get asymptotic confidence intervals for Poisson rate parameter and false-negative rate parameter. The coverage and width properties for various sample size and parameter configurations are studied via a simulation study. Finally, we apply the MLEs and confidence intervals to one real data set and another realistic …


Distribution Of A Sum Of Random Variables When The Sample Size Is A Poisson Distribution, Mark Pfister Aug 2018

Distribution Of A Sum Of Random Variables When The Sample Size Is A Poisson Distribution, Mark Pfister

Electronic Theses and Dissertations

A probability distribution is a statistical function that describes the probability of possible outcomes in an experiment or occurrence. There are many different probability distributions that give the probability of an event happening, given some sample size n. An important question in statistics is to determine the distribution of the sum of independent random variables when the sample size n is fixed. For example, it is known that the sum of n independent Bernoulli random variables with success probability p is a Binomial distribution with parameters n and p: However, this is not true when the sample size …


Generalized Spatiotemporal Modeling And Causal Inference For Assessing Treatment Effects For Multiple Groups For Ordinal Outcome., Soutik Ghosal Aug 2018

Generalized Spatiotemporal Modeling And Causal Inference For Assessing Treatment Effects For Multiple Groups For Ordinal Outcome., Soutik Ghosal

Electronic Theses and Dissertations

This dissertation consists of three projects and can be categorized in two broad research areas: generalized spatiotemporal modeling and causal inference based on observational data. In the first project, I introduce a Bayesian hierarchical mixed effect hurdle model with a nested random effect structure to model the count for primary care providers and understand their spatial and temporal variation. This study further enables us to identify the health professional shortage areas and the possible impacting factors. In the second project, I have unified popular parametric and nonparametric propensity score-based methods to assess the treatment effect of multiple groups for ordinal …


Spatio-Temporal Dynamics Of Atlantic Cod Bycatch In The Maine Lobster Fishery And Its Impacts On Stock Assessment, Robert E. Boenish May 2018

Spatio-Temporal Dynamics Of Atlantic Cod Bycatch In The Maine Lobster Fishery And Its Impacts On Stock Assessment, Robert E. Boenish

Electronic Theses and Dissertations

Of the most iconic fish species in the world, the Atlantic cod (Gadus morhua, hereafter, cod) has been a mainstay in the North Atlantic for centuries. While many global fish stocks have received increased pressure with the advent of new, more efficient fishing technology in the mid-20th century, exceptional pressure has been placed on this prized gadoid. Bycatch, or the unintended catch of organisms, is one of the biggest global fisheries issues. Directly resulting from the failed recovery of cod in the GoM, attention has been placed as to possible sources of unaccounted catch. Among the most …


Geostatistical Analysis Of Potential Sinkhole Risk: Examining Spatial And Temporal Climate Relationships In Tennessee And Florida, Kimberly Blazzard May 2018

Geostatistical Analysis Of Potential Sinkhole Risk: Examining Spatial And Temporal Climate Relationships In Tennessee And Florida, Kimberly Blazzard

Electronic Theses and Dissertations

Sinkholes are a significant hazard for the southeastern United States. Although differences in climate are known to affect karst environments differently, quantitative analyses correlating sinkhole formation with climate variables is lacking. A temporal linear regression for Florida sinkholes and two modeled regressions for Tennessee sinkholes were produced: a general linearized logistic regression and a MaxEnt derived species distribution model. Temporal results showed highly significant correlations with precipitation, teleconnection patterns, temperature, and CO2, while spatial results showed highly significant correlations with precipitation, wind speed, solar radiation, and maximum temperature. Regression results indicated that some sinkhole formation variability could be …


Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard May 2018

Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard

Electronic Theses and Dissertations

Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …


Some New And Generalized Distributions Via Exponentiation, Gamma And Marshall-Olkin Generators With Applications, Hameed Abiodun Jimoh Jan 2018

Some New And Generalized Distributions Via Exponentiation, Gamma And Marshall-Olkin Generators With Applications, Hameed Abiodun Jimoh

Electronic Theses and Dissertations

Three new generalized distributions developed via completing risk, gamma generator, Marshall-Olkin generator and exponentiation techniques are proposed and studied. Structural properties including quantile functions, hazard rate functions, moment, conditional moments, mean deviations, R\'enyi entropy, distribution of order statistics and maximum likelihood estimates are presented. Monte Carlo simulation is employed to examine the performance of the proposed distributions. Applications of the generalized distributions to real lifetime data are presented to illustrate the usefulness of the models.