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A Simulation of Data Censored Rigth Type I with Weibull Distribution

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Detalhes bibliográficos
Resumo:In the maintenance and reliability field, there are frequent analyses with data being censored. In reliability research, many articles do simulation, but few explain how they do it. the loss of information resulting from the unavailable exact failure times will impact negatively the efficiency of reliability analysis. This paper presents four different algorithms to generate random data with a different number of censored values. The four algorithms are compared, and tree parameters are used to select the best one. The Weibull distribution is used to generate the random numbers because it is one of the most used in reliability studies. The results of the algorithm chosen are very relevant; with a sample of n = 50 and a number of cycles of simulations m = 1000, the standard deviation is higher when the shape factor of Weibull distribution is beta = 0.5 and slowly decreases until the shape factor equals 5. The percentage error (PE), one of the indicators selected, is much higher when the percentage of censored data is c = 5%, then goes down when the shape factor increases. There is a different behaviour when censored data is C = 20% and the percentage error (PE) is higher when shape factor is beta = 1.5. This article presents an algorithm that it considers the best for simulating right-censored type-I data. The algorithm has excellent accuracy, random data i.i.d and excellent computational performance.
Autores principais:Gaspar, Daniel
Outros Autores:Andrande Ferreira, Luis
Assunto:Reliability Weibull distribution Algorithm simulation Data censored
Ano:2022
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Viseu
Idioma:inglês
Origem:Repositório Científico do Instituto Politécnico de Viseu
Descrição
Resumo:In the maintenance and reliability field, there are frequent analyses with data being censored. In reliability research, many articles do simulation, but few explain how they do it. the loss of information resulting from the unavailable exact failure times will impact negatively the efficiency of reliability analysis. This paper presents four different algorithms to generate random data with a different number of censored values. The four algorithms are compared, and tree parameters are used to select the best one. The Weibull distribution is used to generate the random numbers because it is one of the most used in reliability studies. The results of the algorithm chosen are very relevant; with a sample of n = 50 and a number of cycles of simulations m = 1000, the standard deviation is higher when the shape factor of Weibull distribution is beta = 0.5 and slowly decreases until the shape factor equals 5. The percentage error (PE), one of the indicators selected, is much higher when the percentage of censored data is c = 5%, then goes down when the shape factor increases. There is a different behaviour when censored data is C = 20% and the percentage error (PE) is higher when shape factor is beta = 1.5. This article presents an algorithm that it considers the best for simulating right-censored type-I data. The algorithm has excellent accuracy, random data i.i.d and excellent computational performance.