Re: Equation of this curve?

Quote:

Originally Posted by

**SamstaUK** (Apologies if I have posted this in the wrong section)

I'm working on a project for my Computing class, and I was wondering what the formula for this curve would be?

http://4.bp.blogspot.com/_dsO7rZ36lc...ence+Curve.jpg
Any help would be very much appreciated (Happy)

Do you have any data values, or can you read them off the curve? If so, you should be able to use a Least-Squares regression to get a polynomial of the same order as the number of data values.

Re: Equation of this curve?

I can't get values with much precision, only where whole values on the y axis intercept the curve.

Someone gave me this formula for the curve, I really don't understand it!

http://home.trainingpeaks.com/media/66910/image001.jpg

Quote:

Where *p*_{t} is the performance at any time *t*, *p*_{0} is the initial performance, *k*_{a} and *k*_{f} (or *k*_{1} and *k*_{2}) are gain terms relating the magnitudes of the positive adaptive and negative fatigue effects (and also serving to convert the units used to quantify training to the units used to quantify performance),* τ*_{a} and *τ*_{f} (or *τ*_{1} and *τ*_{2}) are time constants describing the rate of decay of the positive adaptive and negative fatigue effects, and *w*_{s} is the daily dose of training. The model therefore has four adjustable parameters, i.e., *k*_{a} and *k*_{f} (or *k*_{1} and *k*_{2}) and* τ*_{a} and *τ*_{f} (or *τ*_{1} and *τ*_{2}), which are constrained such that *k*_{a}<*k*_{f} (or *k*_{1}<*k*_{2}) and *τ*_{a}>*τ*_{f} (or *τ*_{1}>*τ*_{2}).

Does anyone know how I could simplify that?

Re: Equation of this curve?

Okay I found it out, I plotted two exponentially weighted moving averages, one with a time period of 42 days and another with 7 days, the curve above is the difference between the two. Thank you Dr. Andrew Coggan! (The person who's work I'm trying to implement)