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PENAKSIRAN PARAMETER ANALISIS REGRESI COX DAN ANALISIS SURVIVAL BAYESIAN
Author(s) -
Rina Wijayanti
Publication year - 2019
Publication title -
prismatika
Language(s) - English
Resource type - Journals
eISSN - 2656-4181
pISSN - 2654-6140
DOI - 10.33503/prismatika.v1i2.427
Subject(s) - bayesian probability , statistics , bayesian statistics , mathematics , bayesian linear regression , markov chain monte carlo , econometrics , computer science , bayesian inference
In the theory of estimation, there are two approaches, namely the classical statistical approach and global statistical approach (Bayesian). Classical statistics are statistics in which the procedure is the decision based only on the data samples taken from the population. While Bayesian statistics in making decisions based on new information from the observed data (sample) and prior knowledge. At this writing Cox Regression Analysis will be taken as an example of parameter estimation by the classical statistical approach Survival Analysis and Bayesian statistical approach as an example of global (Bayesian). Survival Bayesial parameter estimation using MCMC algorithms for model complex / complicated and difficult to resolve while the Cox regression models using the method of partial likelihood. Results of the parameter estimates do not close form that needs to be done by the method of Newton-Raphson iteration.

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