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Semiparametric Bootstrapping for Estimating Parameters of Kriging Model in Deterministic Simulation
Elmanani Simamora (a*), Susiana (b), Eri Widyastuti (b)

a) Department of Mathematics of Faculty of Mathematics and Natural Sciences, State University of Medan, Jalan Willem Iskandar/Pasar V, Medan 20221, Indonesia
*elmanani_simamora[at]unimed.ac.id
b)Department of Mathematics of Faculty of Mathematics and Natural Sciences, State University of Medan, Jalan Willem Iskandar/Pasar V, Medan 20221, Indonesia


Abstract

In practice, the parameters in the kriging model are unknown, but they can be estimated based on the behavior 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

Keywords: Kriging; regression; Simulation; Deterministic ; Semiparametric; Bootstrapping

Topic: Applied Mathematics and statistics

Link: https://ifory.id/abstract/EuZAvp8KWjkd

Conference: International Conference on Science and Technology Applications (ICOSTA 2019)

Plain Format | Corresponding Author (Elmanani Simamora)

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