Author
Zubair Ahmad
Other affiliations: Quaid-i-Azam University
Bio: Zubair Ahmad is an academic researcher from Yazd University. The author has contributed to research in topics: Weibull distribution & Estimator. The author has an hindex of 10, co-authored 67 publications receiving 310 citations. Previous affiliations of Zubair Ahmad include Quaid-i-Azam University.
Papers
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TL;DR: In the last couple of years, the branch of statistics has received a great deal of attention and quite a few new generalized class of distributions have been introduced as discussed by the authors, which is an old practice and has been considered as precious as many other practical problems in statistics.
Abstract: The generalization of the classical distributions is an old practice and has been considered as precious as many other practical problems in statistics. These generalizations started with the introduction of the additional location, scale or shape parameters. In the last couple of years, this branch of statistics has received a great deal of attention and quite a few new generalized class of distributions have been introduced. We present a brief survey of this branch and introduce several new families as well.
48 citations
TL;DR: In this paper, the authors used X-ray diffraction technique to determine the crystal structure, phase purity and average crystallite size of these ferrites nanoparticles, and Sauter's relation was also used to estimate the specific surface area of these nanoparticles.
Abstract: Ferrites ‘MFe2O4 (M = Co, Mg, Cr and Mn)’ nanoparticles were successfully synthesized by chemical co-precipitation method. X-ray diffraction technique was used to determine the crystal structure, phase purity and average crystallite size of these ferrites nanoparticles. X-ray density and porosity were calculated by using standard relations. Sauter’s relation was also used to estimate the specific surface area of these nanoparticles. The important characteristics like morphology, size and shape of these nanoparticles were examined and estimated by scanning electron microscopy technique. The energy-dispersive X-ray spectroscopy was used to determine the elemental compositional of these ferrites nanoparticles. The vibrational modes and bond coordination among the various atoms of these ferrites nanoparticles were investigated by Fourier transform infrared spectroscopy. The frequency-dependent dielectric and impedance measurements were taken by LCR meter. The comparative analysis of dielectric parameters of these ferrites nanoparticles can help the audience to select the material having desired dielectric properties for energy storage practical applications especially lithium-ion batteries.
36 citations
TL;DR: In this paper, a new family of univariate distributions generated from the Weibull random variable, called a new weibull-X family of distributions, is proposed and three useful characterizations based on truncated moments are presented.
Abstract: We propose a new family of univariate distributions generated from the Weibull random variable, called a new Weibull-X family of distributions. Two special sub-models of the proposed family are presented and the shapes of density and hazard functions are investigated. General expressions for some statistical properties are discussed. For the new family, three useful characterizations based on truncated moments are presented. Three different methods to estimate the model parameters are discussed. Monti Carlo simulation study is conducted to evaluate the performances of these estimators. Finally, the importance of the new family is illustrated empirically via two real life applications.
33 citations
TL;DR: In this paper, a new method is suggested to expand a family of life distributions by adding an additional parameter, which may be named as the Zubair-G family of distributions, and general expressions for some mathematical properties are derived.
Abstract: In this article, a new method is suggested to expand a family of life distributions by adding an additional parameter. The new proposal may be named as the Zubair-G family of distributions. For this family, general expressions for some mathematical properties are derived. The maximum product spacing, ordinary least square and maximum likelihood methods are discussed to estimate the model parameters. A three-parameter special sub-model of the proposed family, called the Zubair–Weibull distribution is considered in detail. Its density function can be symmetrical, left-skewed, right-skewed, and has increasing, decreasing, bathtub and upside-down bathtub shaped failure rates. To illustrate the importance of the proposed family over the other well-known methods, two applications to real data sets are analyzed.
32 citations
TL;DR: A convenient method of data comparison that can be helpful for both the governmental and private organizations is provided and a statistical model is suggested to provide a best description of the COVID-19 total death data in the Asian countries.
Abstract: In the current scenario, the outbreak of a pandemic disease COVID-19 is of great interest A broad statistical analysis of this event is still to come, but it is immediately needed to evaluate the disease dynamics in order to arrange the appropriate quarantine activities, to estimate the required number of places in hospitals, the level of individual protection, the rate of isolation of infected persons, and among others In this article, we provide a convenient method of data comparison that can be helpful for both the governmental and private organizations Up to date, facts and figures of the total the confirmed cases, daily confirmed cases, total deaths, and daily deaths that have been reported in the Asian countries are provided Furthermore, a statistical model is suggested to provide a best description of the COVID-19 total death data in the Asian countries
29 citations
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01 Jan 2016
TL;DR: The table of integrals series and products is universally compatible with any devices to read and is available in the book collection an online access to it is set as public so you can get it instantly.
Abstract: Thank you very much for downloading table of integrals series and products. Maybe you have knowledge that, people have look hundreds times for their chosen books like this table of integrals series and products, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. table of integrals series and products is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the table of integrals series and products is universally compatible with any devices to read.
4,085 citations
TL;DR: In this paper, the authors proposed a linear estimator based on order statistics for estimating the likelihood of a given sample with respect to a set of selected order statistics, based on a regression model.
Abstract: List of Tables. List of Figures. Introduction. Basic Theory. Moments and Other Expected Values. Linear Estimation Based on Order Statistics. Maximum Likelihood Estimation. Approximate Maximum Likelihood Estimation. Optimal Linear Estimation Based on Selected Order Statistics. Cohen -Whitten Estimators: Using Order Statistics.Estimation in Regression Models. A Sample Completion Technique for Censored Samples. Bibliography. Index.
342 citations
TL;DR: This book aims to introduce simulation techniques for practitioners in the financial and risk management industry at an intermediate level by having extensive simulation examples using S–PLUS or Visual Basics.
Abstract: (2007). Stochastic Ageing and Dependence for Reliability. Technometrics: Vol. 49, No. 2, pp. 222-222.
314 citations
TL;DR: In the last couple of years, the branch of statistics has received a great deal of attention and quite a few new generalized class of distributions have been introduced as discussed by the authors, which is an old practice and has been considered as precious as many other practical problems in statistics.
Abstract: The generalization of the classical distributions is an old practice and has been considered as precious as many other practical problems in statistics. These generalizations started with the introduction of the additional location, scale or shape parameters. In the last couple of years, this branch of statistics has received a great deal of attention and quite a few new generalized class of distributions have been introduced. We present a brief survey of this branch and introduce several new families as well.
48 citations
TL;DR: In this article, the authors applied selected deep learning models including multilayer perceptron, random forest, and different versions of long shortterm memory (LSTM), using three data sources to train the models, including COVID-19 occurrences, basic information like coded country names, and detailed information like population, and area of different countries.
Abstract: COVID-19 has led to a pandemic, affecting almost all countries in a few months. In this work, we applied selected deep learning models including multilayer perceptron, random forest, and different versions of long short-term memory (LSTM), using three data sources to train the models, including COVID-19 occurrences, basic information like coded country names, and detailed information like population, and area of different countries. The main goal is to forecast the outbreak in nine countries (Iran, Germany, Italy, Japan, Korea, Switzerland, Spain, China, and the USA). The performances of the models are measured using four metrics, including mean average percentage error (MAPE), root mean square error (RMSE), normalized RMSE (NRMSE), and R 2. The best performance was found for a modified version of LSTM, called M-LSTM (winner model), to forecast the future trajectory of the pandemic in the mentioned countries. For this purpose, we collected the data from January 22 till July 30, 2020, for training, and from 1 August 2020 to 31 August 2020, for the testing phase. Through experimental results, the winner model achieved reasonably accurate predictions (MAPE, RMSE, NRMSE, and R 2 are 0.509, 458.12, 0.001624, and 0.99997, respectively). Furthermore, we stopped the training of the model on some dates related to main country actions to investigate the effect of country actions on predictions by the model.
43 citations