Author
Gholamhossein G. Hamedani
Bio: Gholamhossein G. Hamedani is an academic researcher from Marquette University. The author has contributed to research in topics: Order statistic & Weibull distribution. The author has an hindex of 16, co-authored 92 publications receiving 939 citations.
Papers published on a yearly basis
Papers
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TL;DR: A new family of continuous distributions called the odd generalized exponential family, whose hazard rate could be increasing, decreasing, J, reversed-J, bathtub and upside-down bathtub is proposed, which includes as a special case the widely known exponentiated-Weibull distribution.
Abstract: We propose a new family of continuous distributions called the odd generalized exponential family, whose hazard rate could be increasing, decreasing, J, reversed-J, bathtub and upside-down bathtub. It includes as a special case the widely known exponentiated-Weibull distribution. We present and discuss three special models in the family. Its density function can be expressed as a mixture of exponentiated densities based on the same baseline distribution. We derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, Bonferroni and Lorenz curves, Shannon and Renyi entropies and order statistics. For the first time, we obtain the generating function of the Frechet distribution. Two useful characterizations of the family are also proposed. The parameters of the new family are estimated by the method of maximum likelihood. Its usefulness is illustrated by means of two real lifetime data sets.
AMS Subject Classification Primary 60E05; secondary 62N05; 62F10
125 citations
TL;DR: A new class of continuous distributions called the transmuted exponentiated generalized-G family is introduced which extends the exponentiated G class introduced by Cordeiro et al. (2013) and some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Renyi and Shannon entropies, order statistics and probability weighted moments are derived.
Abstract: We introduce a new class of continuous distributions called the transmuted exponentiated generalized-G family which extends the exponentiated generalized-G class introduced by Cordeiro et al. (2013). We provide some special models for the new family. Some of its mathematical properties including explicit expressions for the ordinary and incomplete moments, generating function, Renyi and Shannon entropies, order statistics and probability weighted moments are derived. The estimation of the model parameters is performed by maximum likelihood. The flexibility of the proposed family is illustrated by means of an applications to real dataset.
105 citations
TL;DR: The Kumaraswamy Marshal-Olkin generalized family of distributions as discussed by the authors is a family of continuous distributions with a density function that is symmetric, left-skewed, right-skedwed and reversed-J shaped.
90 citations
TL;DR: In this article, the authors introduce a new family of continuous distributions and study the mathematical properties of the new family, which are based on the ratio of two truncated moments and hazard function.
Abstract: We introduce a new family of continuous distributions and study the mathematical properties of the new family. Some useful characterizations based on the ratio of two truncated moments and hazard function are also presented. We estimate the model parameters by the maximum likelihood method and assess its performance based on biases and mean squared errors in a simulation study framework.
77 citations
TL;DR: In this article, a new generator based on the Weibull random variable is introduced, which has a density function that can be symmetrical, left-skewed, right-swed, bathtub and reversed-J shaped, and has increasing, decreasing and decreasing hazard rates.
Abstract: Statistical analysis of lifetime data is an important topic in reliability engineering, biomedical and social sciences and others. We introduce a new generator based on the Weibull random variable called the new Weibull-G family. We study some of its mathematical properties. Its density function can be symmetrical, left-skewed, right-skewed, bathtub and reversed-J shaped, and has increasing, decreasing, bathtub, upside-down bathtub, J, reversed-J and S shaped hazard rates. Some special models are presented. We obtain explicit expressions for the ordinary and incomplete moments, quantile and generating functions, Renyi entropy, order statistics and reliability. Three useful characterizations based on truncated moments are also proposed for the new family. The method of maximum likelihood is used to estimate the model parameters. We illustrate the importance of the family by means of two applications to real data sets.
70 citations
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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 this article, Statistical Methods for Survival Data Analysis (SVMDA) is used to analyze survival data in the context of statistical methods for survival data analysis (SDFA).
Abstract: (1993). Statistical Methods for Survival Data Analysis. Technometrics: Vol. 35, No. 1, pp. 101-101.
272 citations
01 Jan 2016
TL;DR: In this paper, plots transformations and regression is used as an introduction to graphical methods of diagnostic regression analysis, but end up in malicious downloads, instead of reading a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their laptop.
Abstract: Thank you very much for reading plots transformations and regression an introduction to graphical methods of diagnostic regression analysis. Maybe you have knowledge that, people have look numerous times for their favorite readings like this plots transformations and regression an introduction to graphical methods of diagnostic regression analysis, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their laptop.
138 citations
TL;DR: A new family of continuous distributions called the odd generalized exponential family, whose hazard rate could be increasing, decreasing, J, reversed-J, bathtub and upside-down bathtub is proposed, which includes as a special case the widely known exponentiated-Weibull distribution.
Abstract: We propose a new family of continuous distributions called the odd generalized exponential family, whose hazard rate could be increasing, decreasing, J, reversed-J, bathtub and upside-down bathtub. It includes as a special case the widely known exponentiated-Weibull distribution. We present and discuss three special models in the family. Its density function can be expressed as a mixture of exponentiated densities based on the same baseline distribution. We derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, Bonferroni and Lorenz curves, Shannon and Renyi entropies and order statistics. For the first time, we obtain the generating function of the Frechet distribution. Two useful characterizations of the family are also proposed. The parameters of the new family are estimated by the method of maximum likelihood. Its usefulness is illustrated by means of two real lifetime data sets.
AMS Subject Classification Primary 60E05; secondary 62N05; 62F10
125 citations