首页|Multivariate elliptical-based Birnbaum-Saunders kernel density estimation for nonnegative data
Multivariate elliptical-based Birnbaum-Saunders kernel density estimation for nonnegative data
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NSTL
Elsevier
The Birnbaum-Saunders distribution has been generalized in various ways, for parametric or nonparametric statistical inference. In this paper, as a remedy for the boundary bias problem of nonparametric density estimation, a family of deformed multivariate elliptical-based non-central Birnbaum-Saunders kernel density estimators is introduced, and its asymptotic mean integrated squared error is discussed. The simulation results reveal that a novel log-elliptical density estimator has a good performance in small sample size. (c) 2021 Elsevier Inc. All rights reserved.
Boundary bias problemElliptical-based Birnbaum-Saunders distributionLog-elliptical distributionMultivariate density estimationMULTIPLICATIVE BIAS CORRECTIONFAMILYDISTRIBUTIONSINVERSE
NSTL
Elsevier
