[R] Fitting Production Curves

[Bert Gunter]

This list doesn't do statistics -- it does R programming, though statistics
does occur incidentally sometimes in that context. Not in your post
though. You should post on a statistics site like stats.stackexchange.com
for statistics questions.

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Thu, Sep 20, 2018 at 10:38 PM mikorym via R-help <r-help using r-project.org>
wrote:

> Hi All,
>
> By a production curve I mean for example the output of a mine, peak oil
> production or the yield of a farm over time within the same season. It is
> this last example that we should take as the prototypical case.
>
> What I would like to do is to fit a curve that inherits qualities of the
> discrete production data (such as area of the curve equaling the total
> production for the season). Fitting a curve with least squares (such as a
> Gaussean or Hubbert) presents some issues (with regards to accuracy of
> inherited features). My next logical attempt would be to fit a sum of
> curves, such as a Fourier or Wavelet sum. Perhaps there is something
> simpler or more flexible in the way I am thinking?
>
> My question is:
>
> 1. What would be an effective approach be to fit generalised production
> curves?
> 2. If a Wavelet sum is one of the best approaches, what would be a good
> way of implementing such curve fitting (including calculated coefficients)
> in R?
> 3. Is there anything else or another way that I should rather be thinking
> about this instead?
>
> Best regards
> Phillip-Jan van Zyl
> MSc Mathematics, Stellenbosch
>
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