Valparaiso University
Southern Methodist University
Wayne State University
Florida International University
Istanbul Commerce University
University of Akron
Iowa State University
Oscillation Of Nonlinear Third-Order Difference Equations With Mixed Neutral Terms,
2021
Missouri University of Science and Technology
Oscillation Of Nonlinear Third-Order Difference Equations With Mixed Neutral Terms, Jehad Alzabut, Martin Bohner, Said R. Grace
Mathematics and Statistics Faculty Research & Creative Works
In this paper, new oscillation results for nonlinear third-order difference equations with mixed neutral terms are established. Unlike previously used techniques, which often were based on Riccati transformation and involve limsup or liminf conditions for the oscillation, the main results are obtained by means of a new approach, which is based on a comparison technique. Our new results extend, simplify, and improve existing results in the literature. Two examples with specific values of parameters are offered.
Rattle Detection – An Automotive Case Study,
2021
Jaguar Land Rover
Rattle Detection – An Automotive Case Study, Orla Hartley
International Conference on Lean Six Sigma
This case study showcases the use of statistical tools to develop an objective Squeak and Rattle (S&R) measurement and detection test for End Of Line (EOL) sign off in an automotive manufacturing environment. Audio Induced S&R is an unwanted vibration within the vehicle caused by the sound system, impacting on customer perception of vehicle quality. Testing for S&R in an automotive environment has a key challenge; how to robustly detect a rattle at the EOL and thus prevent plant escapes to the customer. The objective test developed used microphones and analysers in order to replace an e subjective listening test. Within the testing equipment settings, the length of the frequency sweep and the volume level of the sweep can be adapted, which in turn influences the output graph of calculated rattle. A Design of Experiment (DOE) was employed to find the optimised parameters required for these factors. The DOE ...
Lecture Notes On Modern Multivariate Statistical Learning-Version Iv,
2021
Iowa State University and Analytics Iowa LLC
Lecture Notes On Modern Multivariate Statistical Learning-Version Iv, Stephen B. Vardeman
Statistics Publications
This set of notes is the most recent reorganization and update-in- progress of Modern Multivariate Statistical Learning course material de- veloped 2009-2020 over 7 offerings of PhD-level courses and 4 offerings of an MS-level course in the Iowa State University Statistics Department, a short course given in the Statistics Group at Los Alamos National Lab, and two offered through Statistical Horizons LLC. Early versions of the courses were based mostly on the topics and organization of The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman, though very substantial parts benefited from Izenman's Modern Multivariate Statis- tical Techniques, and ...
Robust Lag Weighted Lasso For Time Series Model,
2021
University of Al-Qadisiyah, Iraq
Robust Lag Weighted Lasso For Time Series Model, Tahir R. Dikheel, Alaa Q. Yaseen
Journal of Modern Applied Statistical Methods
The lag-weighted lasso was introduced to deal with lag effects when identifying the true model in time series. This method depends on weights to reflect both the coefficient size and the lag effects. However, the lag weighted lasso is not robust. To overcome this problem, we propose robust lag weighted lasso methods. Both the simulation study and the real data example show that the proposed methods outperform the other existing methods.
Parallel Markets In School Choice,
2021
Sabanci University
Parallel Markets In School Choice, Mustafa Oguz Afacan, Piotr Evdokimov, Rustamdjan Hakimov, Bertan Turhan
Economics Working Papers
When applying to schools, students often submit applications to distinct school systems that operate independently, which leads to waste and distortions of stability due to miscoordination. To alleviate this issue, Manjunath and Turhan (2016) introduce the Iterative Deferred Acceptance mechanism (IDA); however, this mechanism is not strategy-proof. We design an experiment to compare the performance of this mechanism under parallel markets (DecDA2) to the classic Deferred Acceptance mechanism with both divided (DecDA) and unified markets (DA). Consistent with the theory, we find that both stability and efficiency are highest under DA, intermediate under DecDA2, and lowest under DecDA. We observe ...
Conditional Standard Error Of Measurement: Classical Test Theory, Generalizability Theory And Many-Facet Rasch Measurement With Applications To Writing Assessment,
2021
University of Notre Dame
Conditional Standard Error Of Measurement: Classical Test Theory, Generalizability Theory And Many-Facet Rasch Measurement With Applications To Writing Assessment, Alan Huebner, Gustaf B. Skar
Practical Assessment, Research, and Evaluation
Writing assessments often consist of students responding to multiple prompts, which are judged by more than one rater. To establish the reliability of these assessments, there exist different methods to disentangle variation due to prompts and raters, including classical test theory, Many Facet Rasch Measurement (MFRM), and Generalizability Theory (G-Theory). Each of these methods defines a standard error of measurement (SEM), which is a quantity that summarizes the overall variability of student scores. However, less attention has been given to conditional SEMs (CSEM), which expresses the variability for scores of individual students. This tutorial summarizes how to obtain CSEMs for ...
Count Data Regression Analysis: Concepts, Overdispersion Detection, Zero-Inflation Identification, And Applications With R,
2021
University of São Paulo
Count Data Regression Analysis: Concepts, Overdispersion Detection, Zero-Inflation Identification, And Applications With R, Luiz Paulo Fávero, Rafael De Freitas Souza, Patrícia Belfiore, Hamilton Luiz Corrêa, Michel F. C. Haddad
Practical Assessment, Research, and Evaluation
In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it addresses two of the most relevant problems commonly found in real-world count datasets, namely overdispersion and zero-inflation. The entire selection approach may be performed using the programme language R, being all commands used throughout the paper availabe for practical purposes. It is worth mentioning that counting regression models are still not widespread within ...
Spatiotemporal Interactions Between Surface Coal Mining And Land Cover And Use Changes,
2021
Public Power Corporation of Greece
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 ...
Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R),
2021
Aligarh Muslim University
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.
Generalized Ratio-Cum-Product Estimator For Finite Population Mean Under Two-Phase Sampling Scheme,
2021
Indian Institute of Technology (ISM) Dhanbad
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 ...
Pairwise Balanced Designs From Cyclic Pbib Designs,
2021
UGC BSR Faculty Fellow, Department of Statistics, Saurashtra University, Rajkot
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.
How To Apply Multiple Imputation In Propensity Score Matching With Partially Observed Confounders: A Simulation Study And Practical Recommendations,
2021
Stanford University
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 ...
Vif-Regression Screening Ultrahigh Dimensional Feature Space,
2021
University of Al-Qadisiyah
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 New Right-Skewed Upside Down Bathtub Shaped Heavy-Tailed Distribution And Its Applications,
2021
Central University of South Bihar, Gaya, India
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.
Penalized Likelihood Estimation Of Gamma Distributed Response Variable Via Corrected Solution Of Regression Coefficients,
2021
University of lbadan, Nigeria
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.
A New Generalized Family Of Distributions For Lifetime Data,
2021
King Abdulaziz University
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.
Two Different Classes Of Shrinkage Estimators For The Scale Parameter Of The Rayleigh Distribution,
2021
University of Veterinary and Animal Sciences, Lahore
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.
A Simple Random Sampling Modified Dual To Product Estimator For Estimating Population Mean Using Order Statistics,
2021
Central University of Rajasthan
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.
Extending Singh-Maddala Distribution,
2021
Al Madina Higher Institute of Management and Technology, Giza, Egypt
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.
On The Level Of Precision Of A Heterogeneous Transfer Function In A Statistical Neural Network Model,
2021
University of Ibadan
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.
