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IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN


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Abstract

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

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Last update: 2024-06-18 02:29:12

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