[R-sig-ME] Distribution family for non-negative lower and, upper bound values

[Highland Statistics Ltd]

Today's Topics:

    1. Distribution family for non-negative lower and upper	bound
       values (Gitu wa Mbui)


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Message: 1
Date: Thu, 24 Dec 2015 11:53:30 +1000
From: Gitu wa Mbui <gitumbui at gmail.com>
To: r-sig-mixed-models at r-project.org
Subject: [R-sig-ME] Distribution family for non-negative lower and
	upper	bound values
Message-ID:
	<CAFPRYfC4TJRX+jTsrNK4W+Hyo3ePisdw-9F3yJ-QR6oaFu2uZg at mail.gmail.com>
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I am running generalized additive mixed models on two response variables
separately. Values in response 1 are non-negative and bounded between 1-2,
while response 2 is also non- negative and bounded between 1-3.

In choosing the distribution for response 1, I have subtracted 1 (to
rescale to between 0-1) and logit transformed before fitting the models
with gaussian family.

As for response 2 (non-negative values between 1-3), I have divided the
values by 3 so as to rescale to between 0-1, before logit transforming and
fitting with gaussian family.

Does this sound like a good approach? if not what are the alternatives,
considering:
- responses 1&2 are not proportions
- I am using lme4 version (gamm4) which is limited on the number of
families that can be fit
- histograms of both responses are pretty flat (non skewed and don't look
anywhere near normal distribution

~ Gitu




Not sure whether you want to hear my suggestion. Perhaps other people have easier approaches.
If both responses come from the same data then you should apply a multivariate model (with
multiple response variables).

You could try a beta distribution, which can be used when your data is between x1 and x2.

Making a histogram of the response variable is a waste of time. Why should it look normal
distributed?

All in all this sounds like an MCMC job. I haven't tried SabreR...maybe it can do a beta distribution.

Kind regards,


Alain Zuur