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R - Comparing BIC Results Between Expectation-Maximization (EM) and Linear Regression (LR) Algorithm

2 messages · Andika Putra Agustian, Sarah Goslee

#
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.
#
Hi Andika,

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.

Sarah

On Wed, Nov 28, 2018 at 11:30 AM Andika Putra Agustian
<andikaputraagustian99 at gmail.com> wrote: