Re: R - Comparing BIC Results Between Expectation-Maximization (EM) and Linear Regression (LR) Algorithm
We don't do homework on this list, and your question is a statistics
question rather than an R question anyway.
That said, googling "interpreting BIC" should get you going, if
talking to your professor and reading your textbook haven't helped.
On Wed, Nov 28, 2018 at 11:30 AM Andika Putra Agustian
<[hidden email]> wrote:
> 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!
> [[alternative HTML version deleted]]
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