Applied Statistics Commons^™

Spatiotemporal Interactions Between Surface Coal Mining And Land Cover And Use Changes, Nikolaos Paraskevis, Aikaterini Servou, Christos Roumpos, Francis Pavloudakis

Journal of Sustainable Mining

Long-term surface mining and land cover and use changes have been evidenced to have a critical relationship. This study conducts trend and correlation analysis by statistical tools to quantitatively evaluate this relationship in the Ptolemais (Northern Greece) coal mining area for the period 1990-2018. Firstly, based on Corine data and satellite images, a relative spatial indicator (RSI) was adopted to describe the mineral land areas. Secondly, land cover and use changes were spatially defined using Corine data and ArcGIS tools. The active mining area was then distinguished by dumping area, using Landsat satellite imagery and mining maps, and finally, mine …

Pairwise Balanced Designs From Cyclic Pbib Designs, D. K. Ghosh, N. R. Desai, Shreya Ghosh

Journal of Modern Applied Statistical Methods

A pairwise balanced designs was constructed using cyclic partially balanced incomplete block designs with either (λ1 – λ2) = 1 or (λ2 – λ1) = 1. This method of construction of Pairwise balanced designs is further generalized to construct it using cyclic partially balanced incomplete block design when |(λ1 – λ2)| = p. The methods of construction of pairwise balanced designs was supported with examples. A table consisting parameters of Cyclic PBIB designs and its corresponding constructed pairwise balanced design is also included.

Generalized Ratio-Cum-Product Estimator For Finite Population Mean Under Two-Phase Sampling Scheme, Gajendra Kumar Vishwakarma, Sayed Mohammed Zeeshan

Journal of Modern Applied Statistical Methods

A method to lower the MSE of a proposed estimator relative to the MSE of the linear regression estimator under two-phase sampling scheme is developed. Estimators are developed to estimate the mean of the variate under study with the help of auxiliary variate (which are unknown but it can be accessed conveniently and economically). The mean square errors equations are obtained for the proposed estimators. In addition, optimal sample sizes are obtained under the given cost function. The comparison study has been done to set up conditions for which developed estimators are more effective than other estimators with novelty. The …

Two Different Classes Of Shrinkage Estimators For The Scale Parameter Of The Rayleigh Distribution, Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan

Journal of Modern Applied Statistical Methods

Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators.

Extending Singh-Maddala Distribution, Mohamed Ali Ahmed

Journal of Modern Applied Statistical Methods

A new distribution, the exponentiated transmuted Singh-Maddala distribution (ETSM), is presented, and three important special distributions are illustrated. Some mathematical properties are obtained, and parameters estimation method is applied using maximum likelihood. Illustrations based on random numbers and a real data set are given.

How To Apply Multiple Imputation In Propensity Score Matching With Partially Observed Confounders: A Simulation Study And Practical Recommendations, Albee Ling, Maria Montez-Rath, Maya Mathur, Kris Kapphahn, Manisha Desai

Journal of Modern Applied Statistical Methods

Propensity score matching (PSM) has been widely used to mitigate confounding in observational studies, although complications arise when the covariates used to estimate the PS are only partially observed. Multiple imputation (MI) is a potential solution for handling missing covariates in the estimation of the PS. However, it is not clear how to best apply MI strategies in the context of PSM. We conducted a simulation study to compare the performances of popular non-MI missing data methods and various MI-based strategies under different missing data mechanisms. We found that commonly applied missing data methods resulted in biased and inefficient estimates, …

A New Right-Skewed Upside Down Bathtub Shaped Heavy-Tailed Distribution And Its Applications, Sandeep Kumar Maurya, Sanjay K. Singh, Umesh Singh

Journal of Modern Applied Statistical Methods

A one parameter right skewed, upside down bathtub type, heavy-tailed distribution is derived. Various statistical properties and maximum likelihood approaches for estimation purpose are studied. Five different real data sets with four different models are considered to illustrate the suitability of the proposed model.

On The Level Of Precision Of A Heterogeneous Transfer Function In A Statistical Neural Network Model, Christopher Godwin Udomboso

Journal of Modern Applied Statistical Methods

A heterogeneous function of the statistical neural network is presented from two transfer functions: symmetric saturated linear and hyperbolic tangent sigmoid. The precision of the derived heterogeneous model over their respective homogeneous forms are established, both at increased sample sizes hidden neurons. Results further show the sensitivity of the heterogeneous model to increase in hidden neurons.

A New Generalized Family Of Distributions For Lifetime Data, Maha A. D. Aldahlan, Mohamed G. Khalil, Ahmed Z. Afify

Journal of Modern Applied Statistical Methods

A new class of continuous distributions called the generalized Burr X-G family is introduced. Some special models of the new family are provided. Some of its mathematical properties including explicit expressions for the quantile and generating functions, ordinary and incomplete moments, order statistics and Rényi entropy are derived. The maximum likelihood is used for estimating the model parameters. The flexibility of the generated family is illustrated by means of two applications to real data sets.

Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R), Mohammed H. A. Abujarad, Athar Ali Khan

Journal of Modern Applied Statistical Methods

An attempt is made to fit three distributions, the Lomax, exponential Lomax, and Weibull Lomax to implement Bayesian methods to analyze Myeloma patients using Stan. This model is applied to a real survival censored data so that all the concepts and computations will be around the same data. A code was developed and improved to implement censored mechanism throughout using rstan. Furthermore, parallel simulation tools are also implemented with an extensive use of rstan.

Vif-Regression Screening Ultrahigh Dimensional Feature Space, Hassan S. Uraibi

Journal of Modern Applied Statistical Methods

Iterative Sure Independent Screening (ISIS) was proposed for the problem of variable selection with ultrahigh dimensional feature space. Unfortunately, the ISIS method transforms the dimensionality of features from ultrahigh to ultra-low and may result in un-reliable inference when the number of important variables particularly is greater than the screening threshold. The proposed method has transformed the ultrahigh dimensionality of features to high dimension space in order to remedy of losing some information by ISIS method. The proposed method is compared with ISIS method by using real data and simulation. The results show this method is more efficient and more reliable …

A Simple Random Sampling Modified Dual To Product Estimator For Estimating Population Mean Using Order Statistics, Sanjay Kumar, Priyanka Chhaparwal

Journal of Modern Applied Statistical Methods

Bandopadhyaya (1980) developed a dual to product estimator using robust modified maximum likelihood estimators (MMLE’s). Their properties were obtained theoretically and supported through simulations studies with generated as well as one real data set. Robustness properties in the presence of outliers and confidence intervals were studied.

Penalized Likelihood Estimation Of Gamma Distributed Response Variable Via Corrected Solution Of Regression Coefficients, Rasaki Olawale Olanrewaju

Journal of Modern Applied Statistical Methods

A Gamma distributed response is subjected to regression penalized likelihood estimations of Least Absolute Shrinkage and Selection Operator (LASSO) and Minimax Concave Penalty via Generalized Linear Models (GLMs). The Gamma related disturbance controls the influence of skewness and spread in the corrected path solutions of the regression coefficients.

Inference For Step-Stress Partially Accelerated Life Test Model With An Adaptive Type-I Progressively Hybrid Censored Data, Showkat Ahmad Lone, Ahmadur Rahman, Tanveer A. Tarray

Journal of Modern Applied Statistical Methods

Consider estimating data of failure times under step-stress partially accelerated life tests based on adaptive Type-I hybrid censoring. The mathematical model related to the lifetime of the test units is assumed to follow Rayleigh distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameter and tampering coefficient. Also, the work is conducted under a traditional Type-I hybrid censoring plan (scheme). A Monte Carlo simulation algorithm is used to evaluate and compare the performances of the estimators of the tempering coefficient and model parameters under both progressively hybrid censoring plans. The comparison is carried out on the basis of …

Weighted Geometric Mean And Its Properties, Ievgen Turchyn

Applications and Applied Mathematics: An International Journal (AAM)

Various means (the arithmetic mean, the geometric mean, the harmonic mean, the power means) are often used as central tendency statistics. A new statistic of such type is offered for a sample from a distribution on the positive semi-axis, the γ-weighted geometric mean. This statistic is a certain weighted geometric mean with adaptive weights. Monte Carlo simulations showed that the γ-weighted geometric mean possesses low variance: smaller than the variance of the 0.20-trimmed mean for the Lomax distribution. The bias of the new statistic was also studied. We studied the bias in terms of nonparametric confidence intervals for the quantiles …

Analysis Of Means (Anom) Concepts And Computations, Kalanka P. Jayalath, Jacob Turner

Applications and Applied Mathematics: An International Journal (AAM)

The classical Analysis of Means (ANOM) is a statistical inferencing procedure and visualization tool to analyze means from experiments with fixed effects. It can serve as an alternative to the Analysis of Variance (ANOVA) procedure that has distinct advantages when determining which effects contributed to an overall test’s significant result. ANOM has been extended to handle numerous situations including robust procedures involving ranks. More recent advancements of this procedure allow one to handle both random, and mixed effect models. In this work, we discuss the recent developments on ANOM methods that are useful in practice, provide examples that illustrate their …

Some Asymptotic Properties Of Conditional Density Function For Functional Data Under Random Censorship, Fatima Akkal, Abbes Rabhi, Latifa Keddani

Applications and Applied Mathematics: An International Journal (AAM)

In this work, we investigate the asymptotic properties of a nonparametric mode of a conditional density when the real response variable is censored and the explanatory variable is valued in a semi- metric space under ergodic data. First of all, we establish asymptotic properties for a conditional density estimator from which we derive an central limit theorem (CLT) of the conditional mode estimator. Simulation study is also presented to illustrate the validity and finite sample performance of the considered estimator.

Nonparametric Relative Error Estimation Via Functional Regressor By The K Nearest Neighbors Smoothing Under Truncation Random Data, Wahiba Bouabsa

Applications and Applied Mathematics: An International Journal (AAM)

The relation between a functional random covariate and a scalar answer due to left truncation by a different random variable is evaluated in this study with the kNN method. In particular, in order to produce a nonparametric kNN regression operator of these functional truncated data as a loss function, we should use mean squared relative error. In number of neighbors, we establish an estimator and assess the uniform consistency performance with the convergence rate. Then, for different levels of computational truncated data, a simulation analysis was carried out on finite-sized samples to show the feasibility of our estimation procedure and …

Theoretical Study Of Mach Number And Compressibility Effect On The Slender Airfoils, Abrar Hoque, Masudar Rahman, Ashabul Hoque

Applications and Applied Mathematics: An International Journal (AAM)

Theoretical development of the velocity potential equation for compressible flow and its various consequences has been presented. The geometrical interpretation of potential equation and conformal mapping technique are discussed where the mappings link the flow around a circular cylinder of a slender airfoil. The lift and drag coefficients are determined for the slender airfoils based on the Mach number and compressibility effects. The calculated lift coefficients show that with the increasing of attack angle it increases linearly and a higher lift coefficient is found for a smaller Mach number for any certain attack angle. Similarly, the drag profiles are determined …

Nonparametric Estimation Of The Conditional Distribution Function For Surrogate Data By The Regression Model, Imane Metmous, Mohammed K. Attouch, Boubaker Mechab, Torkia Merouan

Applications and Applied Mathematics: An International Journal (AAM)

The main objective of this paper is to estimate the conditional cumulative distribution using the nonparametric kernel method for a surrogated scalar response variable given a functional random one. We introduce the new kernel type estimator for the conditional cumulative distribution function (cond-cdf) of this kind of data. Afterward, we estimate the quantile by inverting this estimated cond-cdf and state the asymptotic properties. The uniform almost complete convergence (with rate) of the kernel estimate of this model and the quantile estimator is established. Finally, a simulation study completed to show how our methodology can be adopted.

Data Analysis And Visualization To Dismantle Gender Discrimination In The Field Of Technology, Quinn Bolewicki

Dissertations, Theses, and Capstone Projects

In the United States, a significant population is facing an uphill battle trying to thrive in an industry that has seen exponential growth in recent years. Women, who account for approximately 50.8% of the U.S. population are statistically underpaid and underrepresented in science, technology, engineering, and mathematics (STEM). Despite women-led technology teams establishing a 21% greater return on investment than teams who don’t, and young women largely outperforming men in math according to a 2015 study, there are only three fortune 500 companies led by women, and they comprise only 10% of internet entrepreneurs. Research generates hundreds of articles, infographics, …

Why Does An Ex-Offender Reoffend?, Jacob Rybak

Symposium of Student Scholars

What leads an offender to go back to prison? This researcher has lived in the Georgia State prison system for 3.5 years. Using personal insights as well as analytics, this researcher analyzes Iowa state’s six-year data set tracking recidivism of released offenders and recommends changes to the prison system to address the analytical findings.

The Iowa recidivism data set includes the following information for all offenders: age group, type of release (parole vs different discharges), release year, original offense, and whether they recidivated. For the recidivating offenders, the data set includes the days to return to prison, the type of …

Access To Higher Education: Do Schools “Grant” Success?, Nathaniel Jones

Symposium of Student Scholars

University education can lead to upward income mobility for low-income students. Being exposed to other student’s life experiences that are different from their own may highlight activities and actions that they may want to consider aiding their success. According to the U.S. Bureau of Labor Statistics, the median weekly earnings in 2019 for all workers in the U.S. was $969. Of those, U.S. workers who held bachelor’s degrees earned $1,248. In 2016, the Brookings Institute found that Pell Grant recipients and first-generation student loan borrowers attended universities that had lower graduation rates and higher loan default rates in comparison to …

Reporting Of Eating Disorder Deaths, Katherine Mobley, Amy Hord

Symposium of Student Scholars

Those affected by eating disorders experience disturbances in eating behaviors which are often related to underlying psychiatric disorders such as anxiety, depression, or obsessive-compulsive disorder (Parekh, 2017, Drieberg et al., 1998 p.53). The duplicitous nature of the disorder makes it difficult to diagnose, and the tole it takes on an individual’s physical health makes its mortality rate the second highest among psychiatric disorders (Guinhut et al., 2021 p.130). Even if the correct education and resources are accessible to certain individuals, negative stigmatization about the disorder can make sufferers unlikely to seek help (Becker et al., 2010). Findings from analysis of …

Characterizing The Northern Hemisphere Circumpolar Vortex Through Space And Time, Nazla Bushra

LSU Doctoral Dissertations

This hemispheric-scale, steering atmospheric circulation represented by the circumpolar vortices (CPVs) are the middle- and upper-tropospheric wind belts circumnavigating the poles. Variability in the CPV area, shape, and position are important topics in geoenvironmental sciences because of the many links to environmental features. However, a means of characterizing the CPV has remained elusive. The goal of this research is to (i) identify the Northern Hemisphere CPV (NHCPV) and its morphometric characteristics, (ii) understand the daily characteristics of NHCPV area and circularity over time, (iii) identify and analyze spatiotemporal variability in the NHCPV’s centroid, and (iv) analyze how CPV features relate …

Guidelines For Regression Analysis In Sas And R: A Case Study, Sarah Milligan

Honors Program Theses and Projects

When a player is a free agent, an individual who is able to sign to any team, one wonders what their best option is. Will signing with Team A or Team B provide them with the largest salary? What factors will affect their salary the most? Does last year’s statistics have a strong impact on next year’s salary? These questions can be answered by performing a regression analysis on previous years data. The primary focus of this project is to determine the most important variables related to an NBA salary. Likewise, the statistical programs SAS and R will be compared …

Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh

Publications and Research

Brownian Motion which is also considered to be a Wiener process and can be thought of as a random walk. In our project we had briefly discussed the fluctuations of financial indices and related it to Brownian Motion and the modeling of Stock prices.

Applying Emotional Analysis For Automated Content Moderation, John Shelnutt

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing …

Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn

Finance Undergraduate Honors Theses

When talking about financial instruments correlation is often thrown around as a measure of the relation between two securities. An often more useful or tradeable measure is cointegration. Cointegration is the measure of two securities tendency to revert to an average price over time. In other words, cointegration ignores directionality and only cares about the distance between two securities. For a mean reversion strategy such as statistical arbitrage cointegration proves to be a far more reliable statistical measure of mean reversion, and while it is more reliable than correlation it still has its own problems. One thing to consider is …

Joint Spacing In The Caples Lake Granodiorite Of The Sierra Nevada Batholith In Eldorado National Forest, California: A Comparative Analysis Of Joint Sets And Data Resolution, Jimmy Wood

Theses/Capstones/Creative Projects

Joints are the most common deformation structure in the Earth’s upper crust and exert a significant influence on structural stability, landscape morphology, and fluid flow . Therefore, a greater understanding of fracture parameters (e.g., length, aperture, etc.) allows us to more accurately predict their presence, persistence, and prevalence, in the subsurface . We study the fracture spacing of two sub-orthogonal joint sets—66 NE-246 SW and 330 NW-150 SE—in the Caples Lake granodiorite of the Sierra Nevada Batholith, California. Specifically, we investigate 1) their spacing distributions with a keen interest in power-law (fractal) spacing, 2) distribution comparisons between master and cross …