[R] predicting waste per capita - is a gaussian model correct?

Abby Spurdle @purd|e@@ @end|ng |rom gm@||@com
Mon May 11 00:56:29 CEST 2020


Well, this is 100% off-topic...
And I wasn't planning to answer the OP's question.

However, I disagree with your answer.

> There is no requirement that the dependent variable in a "regression" type
> estimation follows a gaussian distribution.

False.
It's depends on what type of '"regression" type estimation' one uses,
among other things.

> You need a model of the
> process and then use an estimation technique to estimate your model.  If
> effects in your model are additive do not use a log transformation. If
> effects are multiplicative then use a log transformation.

The main question is, does the model satisfy the *assumptions*.

> The choice
> should be determined by the mechanics of the problem and not by the
> statistics.

While a mechanistic understanding is definitely valuable...
If the criteria for a good model vs a bad model, was whether the model
was consistent with mechanistic theory/understanding, then nearly
every statistical model I've seen would be a bad model.
I would say, a good model is one that is useful...

> If you do use a log transformation the trying to reverse the
> process using an exponential transformation will be biased.
> The extent of
> that bias depends on your problem and it would not be possible to estimate
> the significance of the bias without a much greater knowledge of the
> process and data.

Never heard of this before...
But I do note back-transformation is not trivial, and I'm not an
expert on back-transformations.

> I would suggest that you consult a competent
> statistician.

I agree on that part...



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