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Full-Text Articles in Statistics and Probability

Health Risk Tolerance As A Key Determinant Of (Un)Willingness To Behavior Change: Conceptualization And Scale Development, Hyoyeun Jun, Yan Jin Jan 2019

Health Risk Tolerance As A Key Determinant Of (Un)Willingness To Behavior Change: Conceptualization And Scale Development, Hyoyeun Jun, Yan Jin

International Crisis and Risk Communication Conference

After the study of testing determinants of risk tolerance affecting information sharing, this study was conducted as a second step to actually develop the scale for risk tolerance. Firstly, this study followed qualitative steps, such as in-depth interview and focus group, to capture how public describes the situation when they are tolerating the risk, when they knew what the recommended behavior is to relieve the risk. Secondly, this study collected 1000 U.S. public sample for the survey questionnaire that are the items generated from the qualitative steps.


A New Independence Measure And Its Applications In High Dimensional Data Analysis, Chenlu Ke Jan 2019

A New Independence Measure And Its Applications In High Dimensional Data Analysis, Chenlu Ke

Theses and Dissertations--Statistics

This dissertation has three consecutive topics. First, we propose a novel class of independence measures for testing independence between two random vectors based on the discrepancy between the conditional and the marginal characteristic functions. If one of the variables is categorical, our asymmetric index extends the typical ANOVA to a kernel ANOVA that can test a more general hypothesis of equal distributions among groups. The index is also applicable when both variables are continuous. Second, we develop a sufficient variable selection procedure based on the new measure in a large p small n setting. Our approach incorporates marginal information between …


Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data, Jiaying Weng Jan 2019

Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data, Jiaying Weng

Theses and Dissertations--Statistics

The big data era poses great challenges as well as opportunities for researchers to develop efficient statistical approaches to analyze massive data. Sufficient dimension reduction is such an important tool in modern data analysis and has received extensive attention in both academia and industry.

In this dissertation, we introduce inverse regression estimators using Fourier transforms, which is superior to the existing SDR methods in two folds, (1) it avoids the slicing of the response variable, (2) it can be readily extended to solve the high dimensional data problem. For the ultra-high dimensional problem, we investigate both eigenvalue decomposition and minimum …


Unsupervised Learning In Phylogenomic Analysis Over The Space Of Phylogenetic Trees, Qiwen Kang Jan 2019

Unsupervised Learning In Phylogenomic Analysis Over The Space Of Phylogenetic Trees, Qiwen Kang

Theses and Dissertations--Statistics

A phylogenetic tree is a tree to represent an evolutionary history between species or other entities. Phylogenomics is a new field intersecting phylogenetics and genomics and it is well-known that we need statistical learning methods to handle and analyze a large amount of data which can be generated relatively cheaply with new technologies. Based on the existing Markov models, we introduce a new method, CURatio, to identify outliers in a given gene data set. This method, intrinsically an unsupervised method, can find outliers from thousands or even more genes. This ability to analyze large amounts of genes (even with missing …


Serial Testing For Detection Of Multilocus Genetic Interactions, Zaid T. Al-Khaledi Jan 2019

Serial Testing For Detection Of Multilocus Genetic Interactions, Zaid T. Al-Khaledi

Theses and Dissertations--Statistics

A method to detect relationships between disease susceptibility and multilocus genetic interactions is the Multifactor-Dimensionality Reduction (MDR) technique pioneered by Ritchie et al. (2001). Since its introduction, many extensions have been pursued to deal with non-binary outcomes and/or account for multiple interactions simultaneously. Studying the effects of multilocus genetic interactions on continuous traits (blood pressure, weight, etc.) is one case that MDR does not handle. Culverhouse et al. (2004) and Gui et al. (2013) proposed two different methods to analyze such a case. In their research, Gui et al. (2013) introduced the Quantitative Multifactor-Dimensionality Reduction (QMDR) that uses the overall …


The Large Contraction Principle And Existence Of Periodic Solutions For Infinite Delay Volterra Difference Equations, Paul W. Eloe, Jaganmohan Jonnalagadda, Youssef Raffoul Jan 2019

The Large Contraction Principle And Existence Of Periodic Solutions For Infinite Delay Volterra Difference Equations, Paul W. Eloe, Jaganmohan Jonnalagadda, Youssef Raffoul

Mathematics Faculty Publications

In this article, we establish sufficient conditions for the existence of periodic solutions of a nonlinear infinite delay Volterra difference equation. (See paper for equation.)

We employ a Krasnosel’skii type fixed point theorem, originally proved by Burton. The primary sufficient condition is not verifiable in terms of the parameters of the difference equation, and so we provide three applications in which the primary sufficient condition is verified.


Statistical Methods For Joint Analysis Of Multiple Phenotypes And Their Applications For Phewas, Xueling Li Jan 2019

Statistical Methods For Joint Analysis Of Multiple Phenotypes And Their Applications For Phewas, Xueling Li

Dissertations, Master's Theses and Master's Reports

Genome-wide association studies (GWAS) have successfully detected tens of thousands of robust SNP-trait associations. Earlier researches have primarily focused on association studies of genetic variants and some well-defined functions or phenotypic traits. Emerging evidence suggests that pleiotropy, the phenomenon of one genetic variant affects multiple phenotypes, is widespread, especially in complex human diseases. Therefore, individual phenotype analyses may lose statistical power to identify the underlying genetic mechanism. Contrasting with single phenotype analyses, joint analysis of multiple phenotypes exploits the correlations between phenotypes and aggregates multiple weak marginal effects and is therefore likely to provide new insights into the functional consequences …


Statistical Methods For Mixed Frequency Data Sampling Models, Yun Liu Jan 2019

Statistical Methods For Mixed Frequency Data Sampling Models, Yun Liu

Dissertations, Master's Theses and Master's Reports

The MIDAS models are developed to handle different sampling frequencies in one regression model, preserving information in the higher sampling frequency. Time averaging has been the traditional parametric approach to handle mixed sampling frequencies. However, it ignores information potentially embedded in high frequency. MIDAS regression models provide a concise way to utilize additional information in HF variables. While a parametric MIDAS model provides a parsimonious way to summarize information in HF data, nonparametric models would maintain more flexibility at the expense of the computational complexity. Moreover, one parametric form may not necessarily be appropriate for all cross-sectional subjects. This thesis …


On The Modified Burr Xii-Power Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Mustafa Ç. Korkmaz, Munir Ahmad Jan 2019

On The Modified Burr Xii-Power Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Mustafa Ç. Korkmaz, Munir Ahmad

Mathematical and Statistical Science Faculty Research and Publications

In this paper, a flexible lifetime distribution with increasing, decreasing and bathtub hazard rate called the Modified Burr XII-Power (MBXII-Power) is developed on the basis of the T-X family technique. The density function of the MBXII-Power is arc, exponential, left-skewed, right-skewed, J, reverse-J and symmetrical shaped. Descriptive measures such as moments, moments of order statistics, incomplete moments, inequality measures, residual life functions and reliability measures are theoretically established. The MBXII-Power distribution is characterized via different techniques. Parameters of the MBXII-Power distribution are estimated using maximum likelihood method. The simulation study is performed on the basis of graphical results to see …


Does It Take Three To Dance The Tango? Organizational Design, Triadic Structures And Boundary Spanning Across Subunits, Stefano Tasselli, Alberto Caimo Jan 2019

Does It Take Three To Dance The Tango? Organizational Design, Triadic Structures And Boundary Spanning Across Subunits, Stefano Tasselli, Alberto Caimo

Articles

In this paper, we investigate the processes of boundary spanning across subunits within organizational networks. We hypothesize that patterns of advice across organizational subunits are explained by different triadic mechanisms depending on the organizational design of the intra-organizational network. In organizational networks characterized by flat hierarchy, we found triadic cyclic closure to be positively associated to boundary spanning across subunits; but when the network reflects an organizational structure with formal hierarchical differentiation among members, then we found triadic transitive closure to be associated to boundary spanning across subunits. We test these predictions in two empirical studies consisting of two organizational …


A Multilayer Exponential Random Graph Modelling Approach For Weighted Networks, Alberto Caimo, Isabella Gollini Jan 2019

A Multilayer Exponential Random Graph Modelling Approach For Weighted Networks, Alberto Caimo, Isabella Gollini

Articles

A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network connectivity structure using a hierarchical multilayer exponential random graph model (ERGM) generative process where each network layer represents a different ordinal dyadic category. The network layers are assumed to be generated by an ERGM process conditional on their closest lower network layers. A crucial advantage of the proposed method is the possibility of adopting the binary network statistics specification to describe both the between-layer and across-layer network processes and thus facilitating the interpretation of the …


On The Generalized Log Burr Iii Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein Hamedani, Azeem Ali, Munir Ahmad Jan 2019

On The Generalized Log Burr Iii Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein Hamedani, Azeem Ali, Munir Ahmad

Mathematical and Statistical Science Faculty Research and Publications

In this paper, we present a generalized log Burr III (GLBIII) distribution developed on the basis of a generalized log Pearson differential equation (GLPE). The density function of the GLBIII is exponential, arc, J, reverse-J, bimodal, left-skewed, right- skewed and symmetrical shaped. The hazard rate function of GLBIII distribution has various shapes such as constant, increasing, decreasing, increasing-decreasing, upside- down bathtub and modified bathtub. Descriptive measures such as quantile function, sub- models, ordinary moments, moments of order statistics, incomplete moments, reliability and uncertainty measures are theoretically established. The GLBIII distribution is characterized via different techniques. Parameters of the GLBIII distribution …


Non-Marginal Decisions: A Novel Bayesian Multiple Testing Procedure, Noirrit Kiran Chandra, Sourabh Bhattacharya Jan 2019

Non-Marginal Decisions: A Novel Bayesian Multiple Testing Procedure, Noirrit Kiran Chandra, Sourabh Bhattacharya

Journal Articles

In this paper, we consider the problem of multiple testing where the hypotheses are dependent. In most of the existing literature, either Bayesian or non-Bayesian, the decision rules mainly focus on the validity of the test procedure rather than actually utilizing the dependency to increase efficiency. Moreover, the decisions regarding different hypotheses are marginal in the sense that they do not depend upon each other directly. However, in realistic situations, the hypotheses are usually dependent, and hence it is desirable that the decisions regarding the dependent hypotheses are taken jointly. In this article, we develop a novel Bayesian multiple testing …


Bayesian Hierarchical Meta-Analysis Of Asymptomatic Ebola Seroprevalence, Peter Brody-Moore Jan 2019

Bayesian Hierarchical Meta-Analysis Of Asymptomatic Ebola Seroprevalence, Peter Brody-Moore

CMC Senior Theses

The continued study of asymptomatic Ebolavirus infection is necessary to develop a more complete understanding of Ebola transmission dynamics. This paper conducts a meta-analysis of eight studies that measure seroprevalence (the number of subjects that test positive for anti-Ebolavirus antibodies in their blood) in subjects with household exposure or known case-contact with Ebola, but that have shown no symptoms. In our two random effects Bayesian hierarchical models, we find estimated seroprevalences of 8.76% and 9.72%, significantly higher than the 3.3% found by a previous meta-analysis of these eight studies. We also produce a variation of this meta-analysis where we exclude …


Generalizability Of Effect Sizes Within Aviation Research: More Samples Are Needed, Rian Mehta, Stephen Rice, Scott Winter, Tyler Spence, Maarten Edwards, Karla Candelaria-Oquendo Jan 2019

Generalizability Of Effect Sizes Within Aviation Research: More Samples Are Needed, Rian Mehta, Stephen Rice, Scott Winter, Tyler Spence, Maarten Edwards, Karla Candelaria-Oquendo

International Journal of Aviation, Aeronautics, and Aerospace

It is often the case that researchers attempt to generalize findings from a single convenience sample to the population. They may also wish to make the claim that the sample effect sizes they discover are reasonably similar to the population parameters. The current study attempts to show that they can be mistaken in this assumption, and that different samples can vary dramatically in effect sizes due to myriad discrepancies, such as demographics, sample size, and random error, among other aspects of the samples. Seven hundred and eighty-one participants were recruited from Amazon’s Mechanical Turk, Florida Institute of Technology, Embry-Riddle Aeronautical …


Mathematically Modeling The Role Of Triglyceride Production On Leptin Resistance, Yu Zhao, Daniel Burkow, Baojun Song Jan 2019

Mathematically Modeling The Role Of Triglyceride Production On Leptin Resistance, Yu Zhao, Daniel Burkow, Baojun Song

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Diet-induced obesity is becoming more common all over the world, which is increasing the prevalence of obesity-induced chronic diseases such as diabetes, coronary heart disease, cancer, and sleep apnea. Many experimental results show that obesity is often associated with an elevated concentration of plasma leptin and triglycerides. Triglycerides inhibit the passage of leptin across the blood–brain barrier (BBB) to signal the hypothalamus to suppress appetite. However, it is still not clear how triglyceride concentration affects leptin transport across the BBB and energy balance. In this paper, we propose a novel ordinary differential equations model describing the role of leptin in …


Use Of Complementary And Alternative Medicine Among People With Cardiovascular Diseases In Southeast Georgia, Chimuanya Okoli, Stacy Carswell, Sewuese Akuse, Kelly L. Sullivan Jan 2019

Use Of Complementary And Alternative Medicine Among People With Cardiovascular Diseases In Southeast Georgia, Chimuanya Okoli, Stacy Carswell, Sewuese Akuse, Kelly L. Sullivan

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Background: Heart disease is a leading cause of death in the United States. Proper treatment of patients with cardiovascular disease is essential and can be challenged by non-disclosed use of complementary or alternative treatments. The objective of this study was to assess which demographics were associated with complementary and alternative medicine (CAM) use and if education affects the use of CAM.

Methods: A cross-sectional survey was conducted among a stratified random sample of residents of Southeastern Georgia. Sampling was stratified by urban/rural residence in order to reach sufficient rural residents. Participants that indicated they had been diagnosed with hypertension or …


Quasi-Likelihood Ratio Tests For Homoscedasticity Of Variance In Linear Regression, Lili Yu, Varadan Sevilimedu, Robert Vogel, Hani Samawi Jan 2019

Quasi-Likelihood Ratio Tests For Homoscedasticity Of Variance In Linear Regression, Lili Yu, Varadan Sevilimedu, Robert Vogel, Hani Samawi

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Two quasi-likelihood ratio tests are proposed for the homoscedasticity assumption in the linear regression models. They require few assumptions than the existing tests. The properties of the tests are investigated through simulation studies. An example is provided to illustrate the usefulness of the new proposed tests.


Regression Tree Construction For Reinforcement Learning Problems With A General Action Space, Anthony S. Bush Jr Jan 2019

Regression Tree Construction For Reinforcement Learning Problems With A General Action Space, Anthony S. Bush Jr

College of Graduate Studies: Theses & Dissertations

Part of the implementation of Reinforcement Learning is constructing a regression of values against states and actions and using that regression model to optimize over actions for a given state. One such common regression technique is that of a decision tree; or in the case of continuous input, a regression tree. In such a case, we fix the states and optimize over actions; however, standard regression trees do not easily optimize over a subset of the input variables\cite{Card1993}. The technique we propose in this thesis is a hybrid of regression trees and kernel regression. First, a regression tree splits over …


Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis Jan 2019

Data Patterns Discovery Using Unsupervised Learning, Rachel A. Lewis

College of Graduate Studies: Theses & Dissertations

Self-care activities classification poses significant challenges in identifying children’s unique functional abilities and needs within the exceptional children healthcare system. The accuracy of diagnosing a child's self-care problem, such as toileting or dressing, is highly influenced by an occupational therapists’ experience and time constraints. Thus, there is a need for objective means to detect and predict in advance the self-care problems of children with physical and motor disabilities. We use clustering to discover interesting information from self-care problems, perform automatic classification of binary data, and discover outliers. The advantages are twofold: the advancement of knowledge on identifying self-care problems in …


Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence, Joshua L. Henderson Jan 2019

Measuring Trace Element Concentrations In Artiodactyl Cannonbones Using Portable X-Ray Fluorescence, Joshua L. Henderson

All Master's Theses

Artiodactyl bones are the most common faunal remains found in Washington prehistoric archaeology sites, but they are often too fragmented to accurately identify a family, genus, or species. Traditional faunal analysis can only organize unidentifiable bone fragments into size class, and chemical methods often require the destruction of bone samples. In this thesis research, I tested a new, nondestructive faunal analysis technique using portable X-ray fluorescence (pXRF) to measure trace element concentrations in comparative collection and archaeological bone samples. Using cannonbones from five different artiodactyl species, I collected trace element data from 50 comparative collection specimens and 18 archaeological specimens …


Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood, Sarbesh R. Pandeya Jan 2019

Variable Selection In Accelerated Failure Time (Aft) Frailty Models: An Application Of Penalized Quasi-Likelihood, Sarbesh R. Pandeya

College of Graduate Studies: Theses & Dissertations

Variable selection is one of the standard ways of selecting models in large scale datasets. It has applications in many fields of research study, especially in large multi-center clinical trials. One of the prominent methods in variable selection is the penalized likelihood, which is both consistent and efficient. However, the penalized selection is significantly challenging under the influence of random (frailty) covariates. It is even more complicated when there is involvement of censoring as it may not have a closed-form solution for the marginal log-likelihood. Therefore, we applied the penalized quasi-likelihood (PQL) approach that approximates the solution for such a …


Safety Constraint Optimization Of Combination Drug Therapy In Hypertension Clinical Trials, Victor Chukwu Jan 2019

Safety Constraint Optimization Of Combination Drug Therapy In Hypertension Clinical Trials, Victor Chukwu

College of Graduate Studies: Theses & Dissertations

In Clinical Practice, combination drug therapy has become common in treating many disease conditions. The purpose of these combinations is often to ensure optimal efficacy and to reduce adverse effects that may arise from monotherapy. Clinical trials have also been conducted to ensure efficacy and safety of these combinations before they are introduced into the market. However, adverse effects still occur with combination therapies. The objective of this study is to (1) To determine a region of optimum doses of Drug A and Drug B in combination while focusing on efficacy alone (2) To determine a region of optimum doses …


Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications, Soliu A. Raheem Jan 2019

Some New Generalized Distribution Via Lindley-Weibuli And Lindley-Log-Logistic Distributions With Applications, Soliu A. Raheem

College of Graduate Studies: Theses & Dissertations

In this thesis, new generalized distributions, namely Beta Lindley-Log-Logistic (BLLLoG) distribution, Marshall-Olkin Lindley-Weibull (MOLW) distribution, and Gamma LindleyWeibull (GLW) distribution as well as related sub-distributions are proposed. Series expansion of the densities are obtained. Statistical properties of these distributions, including hazard function, reverse hazard function, moments, reliability, quantile function, mean deviations, Bonferroni and Lorenz curves, entropy and Fisher information are derived. Method of maximum likelihood is used to estimate the parameters of the new distributions. 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 …


Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos Jan 2019

Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos

Theses and Dissertations--Statistics

This dissertation focuses on the problem of making high-dimensional inference for two or more groups. High-dimensional means both the sample size (n) and dimension (p) tend to infinity, possibly at different rates. Classical approaches for group comparisons fail in the high-dimensional situation, in the sense that they have incorrect sizes and low powers. Much has been done in recent years to overcome these problems. However, these recent works make restrictive assumptions in terms of the number of treatments to be compared and/or the distribution of the data. This research aims to (1) propose and investigate refined …


A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele Jan 2019

A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele

Theses and Dissertations--Statistics

A practical problem often encountered with observed count data is the presence of excess zeros. Zero-inflation in count data can easily be handled by zero-inflated models, which is a two-component mixture of a point mass at zero and a discrete distribution for the count data. In the presence of predictors, zero-inflated Poisson (ZIP) regression models are, perhaps, the most commonly used. However, the fully parametric ZIP regression model could sometimes be restrictive, especially with respect to the mixing proportions. Taking inspiration from some of the recent literature on semiparametric mixtures of regressions models for flexible mixture modeling, we propose a …


Characterizations Of Certain Recently Introduced Discrete Distributions, Gholamhossein G. Hamedani Jan 2019

Characterizations Of Certain Recently Introduced Discrete Distributions, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Characterizations of certain recently introduced discrete distributions are presented to complete, in some way, the works cited in the References.


Wellness Paradigms In Predicting Stress And Burnout Among Beginning Expatriate Teachers, Kimala Proctor Jan 2019

Wellness Paradigms In Predicting Stress And Burnout Among Beginning Expatriate Teachers, Kimala Proctor

Walden Dissertations and Doctoral Studies

Research indicates that the current teacher shortage is in part due to stress and burnout. A topic that has not been examined is beginning expatriate English medium teachers (EMTs) with 5 years or less of teaching experience in the United Arab Emirates and the relationship between using individualized, self-initiated wellness paradigms and stress, job burnout, and intent to leave the teaching profession. The transactional model of stress and coping, Maslach's multidimensional theory of burnout, and the health promotion model were used to evaluate the moderating effects of the EMTs' burnout and stress levels on their wellness and intent to leave. …


Cronbach’S Alpha Under Insufficient Effort Responding: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman Jan 2019

Cronbach’S Alpha Under Insufficient Effort Responding: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman

Psychology: Faculty Publications

Surveys commonly suffer from insufficient effort responding (IER). If not accounted for, IER can cause biases and lead to false conclusions. In particular, Cronbach’s alpha has been empirically observed to either deflate or inflate due to IER. This paper will elucidate how IER impacts Cronbach’s alpha in a variety of situations. Previous results concerning internal consistency under mixture models are extended to obtain a characterization of Cronbach’s alpha in terms of item validities, average variances, and average covariances. The characterization is then applied to contaminating distributions representing various types of IER. The discussion will provide commentary on previous simulation-based investigations, …


Cubic Rank Transmuted Modified Burr Iii Pareto Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Wenhui Sheng, Munir Ahmad Jan 2019

Cubic Rank Transmuted Modified Burr Iii Pareto Distribution: Development, Properties, Characterizations And Applications, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Wenhui Sheng, Munir Ahmad

Mathematical and Statistical Science Faculty Research and Publications

In this paper, a flexible lifetime distribution called Cubic rank transmuted modified Burr III-Pareto (CRTMBIII-P) is developed on the basis of the cubic ranking transmutation map. The density function of CRTMBIII-P is arc, exponential, left-skewed, right-skewed and symmetrical shaped. Descriptive measures such as moments, incomplete moments, inequality measures, residual life function and reliability measures are theoretically established. The CRTMBIII-P distribution is characterized via ratio of truncated moments. Parameters of the CRTMBIII-P distribution are estimated using maximum likelihood method. The simulation study for the performance of the maximum likelihood estimates (MLEs) of the parameters of the CRTMBIII-P distribution is carried out. …