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Author Leiva, V.; Ruggeri, F.; Saulo, H.; Vivanco, J.F.
Title A methodology based on the Birnbaum-Saunders distribution for reliability analysis applied to nano-materials Type
Year 2017 Publication Reliability Engineering & System Safety Abbreviated Journal Reliab. Eng. Syst. Saf.
Volume (down) 157 Issue Pages 192-201
Keywords Bayesian analysis; Hardness data; Markov chain Monte Carlo method; R software
Abstract The Birnbaum-Saunders distribution has been widely studied and applied to reliability studies. This paper proposes a novel use of this distribution to analyze the effect on hardness, a material mechanical property, when incorporating nano-particles inside a polymeric bone cement. A plain variety and two modified types of mesoporous silica nano-particles are considered. In biomaterials, one can study the effect of nano-particles on mechanical response reliability. Experimental data collected by the authors from a micro-indentation test about hardness of a commercially available polymeric bone cement are analyzed. Hardness is modeled with the Birnbaum-Saunders distribution and Bayesian inference is performed to derive a methodology, which allows us to evaluate the effect of using nano-particles at different loadings by the R software. (C) 2016 Elsevier Ltd. All rights reserved.
Address [Leiva, Victor; Vivanco, Juan F.] Univ Adolfo Ibanez, Fac Sci & Engn, Vina del Mar, Chile, Email: victorleivictorleivasanchez@gmail.com
Corporate Author Thesis
Publisher Elsevier Sci Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0951-8320 ISBN Medium
Area Expedition Conference
Notes WOS:000387195700017 Approved
Call Number UAI @ eduardo.moreno @ Serial 676
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Author Wanke, P.; Ewbank, H.; Leiva, V.; Rojas, F.
Title Inventory management for new products with triangularly distributed demand and lead-time Type
Year 2016 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume (down) 69 Issue Pages 97-108
Keywords Approximation of functions; Bisection method; Kernel method; Kullback-Leibler divergence; Monte Carlo method; (Q, r) model; R software; Statistical distributions
Abstract This paper proposes a computational methodology to deal with the inventory management of new products by using the triangular distribution for both demand per unit time and lead-time. The distribution for demand during lead-time (or lead-time demand) corresponds to the sum of demands per unit time, which is difficult to obtain. We consider the triangular distribution because it is useful when a distribution is unknown due to data unavailability or problems to collect them. We provide an approach to estimate the probability density function of the unknown lead-time demand distribution and use it to establish the suitable inventory model for new products by optimizing the associated costs. We evaluate the performance of the proposed methodology with simulated and real-world demand data. This methodology may be a decision support tool for managers dealing with the measurement of demand uncertainty in new products. (C) 2015 Elsevier Ltd. All rights reserved.
Address [Wanke, Peter; Ewbank, Henrique] Univ Fed Rio de Janeiro, COPPEAD Grad Sch Business, BR-21941 Rio De Janeiro, Brazil, Email: victorleivasanchez@gmail.com
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:000370908300009 Approved
Call Number UAI @ eduardo.moreno @ Serial 586
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Author Khosravi, M.; Leiva, V.; Jamalizadeh, A.; Porcu, E.
Title On a nonlinear Birnbaum-Saunders model based on a bivariate construction and its characteristics Type
Year 2016 Publication Communications In Statistics-Theory And Methods Abbreviated Journal Commun. Stat.-Theory Methods
Volume (down) 45 Issue 3 Pages 772-793
Keywords Data analysis; Elliptically contoured distributions; Likelihood and Monte Carlo methods; Linear and nonlinear skew-elliptic distributions
Abstract The Birnbaum-Saunders (BS) distribution is an asymmetric probability model that is receiving considerable attention. In this article, we propose a methodology based on a new class of BS models generated from the Student-t distribution. We obtain a recurrence relationship for a BS distribution based on a nonlinear skew-t distribution. Model parameters estimators are obtained by means of the maximum likelihood method, which are evaluated by Monte Carlo simulations. We illustrate the obtained results by analyzing two real data sets. These data analyses allow the adequacy of the proposed model to be shown and discussed by applying model selection tools.
Address [Khosravi, Mohsen; Jamalizadeh, Ahad] Shahid Bahonar Univ Kerman, Dept Stat, Kerman, Iran, Email: victorleivasanchez@gmail.com
Corporate Author Thesis
Publisher Taylor & Francis Inc Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0361-0926 ISBN Medium
Area Expedition Conference
Notes WOS:000368695100016 Approved
Call Number UAI @ eduardo.moreno @ Serial 576
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Author Sanchez, L.; Leiva, V.; Caro-Lopera, F.J.; Cysneiros, F.J.A.
Title On matrix-variate Birnbaum-Saunders distributions and their estimation and application Type
Year 2015 Publication Brazilian Journal Of Probability And Statistics Abbreviated Journal Braz. J. Probab. Stat.
Volume (down) 29 Issue 4 Pages 790-812
Keywords Computer language; data analysis; elliptically contoured distribution; maximum likelihood estimator; Monte Carlo method; shape theory
Abstract Diverse phenomena from the real-world can be modeled using random matrices, allowing matrix-variate distributions to be considered. The normal distribution is often employed in this modeling, but usually the mentioned random matrices do not follow such a distribution. An asymmetric non-normal model that is receiving considerable attention due to its good properties is the Birnbaum-Saunders (BS) distribution. We propose a statistical methodology based on matrix-variate BS distributions. This methodology is implemented in the statistical software R. A simulation study is conducted to evaluate its performance. Finally, an application with real-world matrix-variate data is carried out to illustrate its potentiality and suitability.
Address [Sanchez, Luis] Univ Valparaiso, Inst Estadist, Valparaiso, Chile, Email: ldaniel9.24@gmail.com;
Corporate Author Thesis
Publisher Brazilian Statistical Association Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0103-0752 ISBN Medium
Area Expedition Conference
Notes WOS:000362310900005 Approved
Call Number UAI @ eduardo.moreno @ Serial 621
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Author Santos-Neto, M.; Cysneiros, F.J.A.; Leiva, V.; Barros, M.
Title A Reparameterized Birnbaum-Saunders Distribution And Its Moments, Estimation And Applications Type
Year 2014 Publication REVSTAT-Statistical Journal Abbreviated Journal REVSTAT-Stat. J.
Volume (down) 12 Issue 3 Pages 247-272
Keywords data analysis; maximum likelihood and moment estimation; Monte Carlo method; random number generation; statistical software
Abstract The Birnbaum-Saunders (BS) distribution is a model that is receiving considerable attention due to its good properties. We provide some results on moments of a reparameterized version of the BS distribution and a generation method of random numbers from this distribution. In addition, we propose estimation and inference for the mentioned parameterization based on maximum likelihood, moment, modified moment and generalized moment methods. By means of a Monte Carlo simulation study, we evaluate the performance of the proposed estimators. We discuss applications of the reparameterized BS distribution from different scientific fields and analyze two real-world data sets to illustrate our results. The simulated and real data are analyzed by using the R software.
Address [Santos-Neto, Manoel; Barros, Michelli] Univ Fed Campina Grande, Dept Estat, Campina Grande, Brazil, Email: manoel.ferreira@ufcg.edu.br;
Corporate Author Thesis
Publisher Inst Nacional Estatistica-Ine Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1645-6726 ISBN Medium
Area Expedition Conference
Notes WOS:000349017700003 Approved
Call Number UAI @ eduardo.moreno @ Serial 448
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