Hi there, I am trying to compare result of BIC (Bayesian Information Criterion) between Expectation-Maximization (EM) and Linear Regression (LR) Algorithm on "Hotel Occupancy" data using R, for my college task.
The data contains data occupancy percentage from January to December 2017, based on islands in Indonesia. The result I got : - for EM : -2687.035 - for LR : 225.0898 *notes : - For EM, I use mclust packages, then I type mclustBIC(variable name) - For LR, I type BIC(MonthA~MonthB) etc (every 2 month), then I count the average as the BIC result. I don't know how to compare it, which BIC result is better (EM or LR)? Can you explain the reason please? Thanks in advance! Regards, Andika. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.