Author
Artur J. Lemonte
Other affiliations: University of São Paulo
Bio: Artur J. Lemonte is an academic researcher from Federal University of Pernambuco. The author has contributed to research in topics: Birnbaum–Saunders distribution & Score test. The author has an hindex of 26, co-authored 81 publications receiving 1964 citations. Previous affiliations of Artur J. Lemonte include University of São Paulo.
Papers
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TL;DR: In this article, a new five-parameter continuous distribution, the so-called McDonald Lomax distribution, was proposed and studied, which has as special sub-models new four-and threeparameter distributions, including expansions for the density function, explicit expressions for the moments, generating and quantile functions, mean deviations and Renyi entropy.
Abstract: A new five-parameter continuous distribution, the so-called McDonald Lomax distribution, that extends the Lomax distribution and some other distributions is proposed and studied. The model has as special sub-models new four- and three-parameter distributions. Various structural properties of the new distribution are derived, including expansions for the density function, explicit expressions for the moments, generating and quantile functions, mean deviations and Renyi entropy. The score function is derived and the estimation is performed by maximum likelihood. We also obtain the observed information matrix. An application illustrates the usefulness of the proposed model.
159 citations
TL;DR: The so-called @b-Birnbaum-Saunders distribution is proposed for fatigue life modeling and various properties of the new model including expansions for the moments, moment generating function, mean deviations, density function of the order statistics and their moments are derived.
134 citations
TL;DR: A new three-parameter exponential-type family of distributions which can be used in modeling survival data, reliability problems and fatigue life studies is introduced and maximum likelihood estimation of the unknown parameters of the new model for complete sample as well as for censored sample is discussed.
110 citations
TL;DR: Nearly unbiased estimators for the two-parameter Birnbaum-Saunders distribution are developed that are bias-free to second order and a Bartlett correction is derived that improves the finite-sample performance of the likelihood ratio test in finite samples.
102 citations
TL;DR: In this article, the authors proposed a generalization of the Kumaraswamy distribution, referred to as the exponentiated KG distribution, and derived the moments, moment generating function, mean deviations, Bonferroni and Lorentz curves, density of the order statistics and their moments.
Abstract: The paper by Kumaraswamy (Journal of Hydrology 46 (1980) 79–88) introduced a probability distribution for double bounded random processes which has considerable attention in hydrology and related areas. Based on this distribution, we propose a generalization of the Kumaraswamy distribution refereed to as the exponentiated Kumaraswamy distribution. We derive the moments, moment generating function, mean deviations, Bonferroni and Lorentz curves, density of the order statistics and their moments. We also present a related distribution, so-called the log-exponentiated Kumaraswamy distribution, which extends the generalized exponential (Aust. N. Z. J. Stat. 41 (1999) 173–188) and double generalized exponential (J. Stat. Comput. Simul. 80 (2010) 159–172) distributions. We discuss maximum likelihood estimation of the model parameters. In applications to real data sets, we show that the log-exponentiated Kumaraswamy model can be used quite effectively in analyzing lifetime data.
95 citations
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01 Jan 2016
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474 citations
TL;DR: A new book enPDFd comparison methods for queues and other stochastic models that can be a new way to explore the knowledge and one thing to always remember in every reading time, even step by step is shown.
Abstract: Studies stochastic models of queueing, reliability, inventory, and sequencing in which random influences are considered. One stochastic mode--rl is approximated by another that is simpler in structure or about which simpler assumptions can be made. After general results on comparison properties of random variables and stochastic processes are given, the properties are illustrated by application to various queueing models and questions in experimental design, renewal and reliability theory, PERT networks and branching processes.
472 citations