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 <

[hidden email]>

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

>

> ______________________________________________

>

[hidden email] mailing list -- To UNSUBSCRIBE and more, see

>

https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide

>

http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.

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