TY - JOUR
T1 - Estimation of extreme percentiles in BirnbaumSaunders distributions
AU - Vilca, Filidor
AU - Santana, Lucia
AU - Leiva, Víctor
AU - Balakrishnan, N.
N1 - Funding Information:
The authors wish to thank the Editor-in-Chief, Prof. Stanley P. Azen, an anonymous Associate Editor and referees for their useful comments and suggestions. This study was partially supported by a CNPq and FAPESP grant from Brazil and by FONDECYT 1080326 and DIPUV 50-2007 grants from Chile.
PY - 2011/4/1
Y1 - 2011/4/1
N2 - The BirnbaumSaunders distribution has recently received considerable attention in the statistical literature, including some applications in the environmental sciences. Several authors have generalized this distribution, but these generalizations are still inadequate for predicting extreme percentiles. In this paper, we consider a variation of the BirnbaumSaunders distribution, which enables the prediction of extreme percentiles as well as the implementation of the EM algorithm for maximum likelihood estimation of the distribution parameters. This implementation has some advantages over the direct maximization of the likelihood function. Finally, we present results of a simulation study along with an application to a real environmental data set.
AB - The BirnbaumSaunders distribution has recently received considerable attention in the statistical literature, including some applications in the environmental sciences. Several authors have generalized this distribution, but these generalizations are still inadequate for predicting extreme percentiles. In this paper, we consider a variation of the BirnbaumSaunders distribution, which enables the prediction of extreme percentiles as well as the implementation of the EM algorithm for maximum likelihood estimation of the distribution parameters. This implementation has some advantages over the direct maximization of the likelihood function. Finally, we present results of a simulation study along with an application to a real environmental data set.
KW - EM and ECM algorithms
KW - Monte Carlo simulations
KW - Skew distributions
UR - http://www.scopus.com/inward/record.url?scp=78650810913&partnerID=8YFLogxK
U2 - 10.1016/j.csda.2010.10.023
DO - 10.1016/j.csda.2010.10.023
M3 - Article
AN - SCOPUS:78650810913
SN - 0167-9473
VL - 55
SP - 1665
EP - 1678
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
IS - 4
ER -