Random number generators for the generalized Birnbaum-Saunders distribution
| Autor: | Gilberto A. Paula, Víctor Leiva, Antonio Sanhueza, Pranab Kumar Sen |
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| Rok vydání: | 2008 |
| Předmět: |
Statistics and Probability
Mathematical optimization Random number generation Applied Mathematics Monte Carlo method Birnbaum–Saunders distribution Inverse Gaussian distribution DISTRIBUIÇÃO ELÍPTICA symbols.namesake Distribution (mathematics) Goodness of fit Modeling and Simulation Outlier symbols Statistical inference Applied mathematics Statistics Probability and Uncertainty Mathematics |
| Zdroj: | Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION Artículos CONICYT CONICYT Chile instacron:CONICYT |
| Popis: | The generalized Birnbaum–Saunders distribution pertains to a class of lifetime models including both lighter and heavier tailed distributions. This model adapts well to lifetime data, even when outliers exist, and has other good theoretical properties and application perspectives. However, statistical inference tools may not exist in closed form for this model. Hence, simulation and numerical studies are needed, which require a random number generator. Three different ways to generate observations from this model are considered here. These generators are compared by utilizing a goodness-of-fit procedure as well as their effectiveness in predicting the true parameter values by using Monte Carlo simulations. This goodness-of-fit procedure may also be used as an estimation method. The quality of this estimation method is studied here. Finally, through a real data set, the generalized and classical Birnbaum–Saunders models are compared by using this estimation method. |
| Databáze: | OpenAIRE |
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