[R] Fitting Production Curves
bgunter@4567 @end|ng |rom gm@||@com
Fri Sep 21 17:28:32 CEST 2018
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though. You should post on a statistics site like stats.stackexchange.com
for statistics questions.
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On Thu, Sep 20, 2018 at 10:38 PM mikorym via R-help <r-help using r-project.org>
> 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
> 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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