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 …
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.
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 …
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.
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.
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, …
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.
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.
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.
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.
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 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.
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.
Inference For Step-Stress Partially Accelerated Life Test Model With An Adaptive Type-I Progressively Hybrid Censored Data,
2021
Saudi Electronic University Riyadh, Saudi Arabia
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,
2021
Oles Honchar Dnipro National University
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,
2021
University of Houston – Clear Lake
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,
2021
University Djillali LIABES of Sidi Bel Abbes
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 Estimation Of The Conditional Distribution Function For Surrogate Data By The Regression Model,
2021
Djillali Liabes University
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.
Nonparametric Relative Error Estimation Via Functional Regressor By The K Nearest Neighbors Smoothing Under Truncation Random Data,
2021
Djillali Liabes University
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,
2021
Military Institute of Science and Technology
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 …
