IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN

This paper studies the implementation of Markov Chain Monte Carlo on estimating the hyperparameter of Gaussian process. Metropolish-Hasting (MH) algorithm is used to generate the random samples from the posterior distribution that can not be generated by a direct simulation method. This algorithm re...

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Bibliographic Details
Main Authors: Moch. Abdul Mukid, Sugito Sugito
Format: Article
Language:English
Published: Universitas Diponegoro 2011-06-01
Series:Media Statistika
Online Access:https://ejournal.undip.ac.id/index.php/media_statistika/article/view/2503
Description
Summary:This paper studies the implementation of Markov Chain Monte Carlo on estimating the hyperparameter of Gaussian process. Metropolish-Hasting (MH) algorithm is used to generate the random samples from the posterior distribution that can not be generated by a direct simulation method. This algorithm require only a proposal distribution for generating a candidate point. In this paper uniform distribution is choosen as the proposal distribution.   Keywords: Markov Chain Monte Carlo, Gaussian Process, Metropolis-Hasting Algorithm
ISSN:1979-3693
2477-0647