Bootstrap-based improved estimators for the two-parameter Birnbaum–Saunders distribution

DOI10.1080/10629360600903882zbMath1367.62037OpenAlexW2074462698MaRDI QIDQ5457922

Alexandre B. Simas, Artur J. Lemonte, Francisco Cribari-Neto

Publication date: 10 April 2008

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10629360600903882

zbMATH Keywords

bootstrapbias correctionBirnbaum-Saunders distributionmaximum-likelihood estimation

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Exact distribution theory in statistics (62E15) Estimation in survival analysis and censored data (62N02)

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Uses Software

• Ox

Cites Work

• Modified moment estimation for the two-parameter Birnbaum-Saunders distribution
• On bootstrap and analytical bias corrections
• Bootstrap methods: another look at the jackknife
• Approximate bias correction in econometrics
• Econometric and statistical computing using Ox
• Improved estimation of clutter properties in speckled imagery.
• Stochastic models of failure in random environments
• On the Relationship between Two Fatigue-Life Models
• Inferences on the Parameters of the Birnbaum-Saunders Fatigue Life Distribution Based on Maximum Likelihood Estimation
• A Family of Random Variables Closed Under Reciprocation
• A moment-generating function with application to the birnbaum-saunders distribution
• Reliability bounds and critical time for the Birnbaum-Saunders distribution
• Parameter estimation for ihe birnbaum-saunders distribution based on symmetrically censored samples
• Percentile bounds and tolerance limits for the birnbaum-saunders distribution
• A new family of life distributions
• Estimation for a family of life distributions with applications to fatigue
• More Efficient Bootstrap Computations
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