Open AccessSemiparametric Bootstrapping Forestimating Parameters in Krigingmodel for Deterministic Simulations
Author(s) -
Elmanani Simamora,
Susiana Susiana,
Eri Widyastuti
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1485/1/012010
Subject(s) - kriging , bootstrapping (finance) , mathematics , semiparametric regression , statistics , regression , econometrics , computer science
In practice, the parameters in the Kriging model are unknown, but they can be estimated based on the behaviour of the observed data. Parameters in the Kriging model can be estimated based on the consideration of Regression-Kriging models. Regression-Kriging models are Universal Kriging models with polynomials of degree zero (Ordinary Kriging), one (Universal Kriging with degree one), or two (Universal Kriging with degree two). A new method for estimating the parameters in the Kriging model with semiparametric bootstrapping is proposed in this paper. The semiparametric bootstrapping procedure works by combining the bootstrap method and Kriging.