IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN

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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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
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spelling doaj-b77363ef439442daac2bbd04fa02c4f82020-11-25T02:48:38ZengUniversitas DiponegoroMedia Statistika1979-36932477-06472011-06-014111010.14710/medstat.4.1.1-102164IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIANMoch. Abdul MukidSugito SugitoThis 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 Algorithmhttps://ejournal.undip.ac.id/index.php/media_statistika/article/view/2503
collection DOAJ
language English
format Article
sources DOAJ
author Moch. Abdul Mukid
Sugito Sugito
spellingShingle Moch. Abdul Mukid
Sugito Sugito
IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
Media Statistika
author_facet Moch. Abdul Mukid
Sugito Sugito
author_sort Moch. Abdul Mukid
title IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
title_short IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
title_full IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
title_fullStr IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
title_full_unstemmed IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
title_sort implementasi markov chain monte carlo pada pendugaan hyperparameter regresi proses gaussian
publisher Universitas Diponegoro
series Media Statistika
issn 1979-3693
2477-0647
publishDate 2011-06-01
description 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
url https://ejournal.undip.ac.id/index.php/media_statistika/article/view/2503
work_keys_str_mv AT mochabdulmukid implementasimarkovchainmontecarlopadapendugaanhyperparameterregresiprosesgaussian
AT sugitosugito implementasimarkovchainmontecarlopadapendugaanhyperparameterregresiprosesgaussian
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