Please follow Doug Bates' advice:
1. Plot the data.
2. Play with the nonlinear formula to understand what the particular coefficients do.
3. Use algorithm = "plinear".
** If you did the above, you would find out that you "data" are entirely linear. What values for the parameters to you need to make your nonlinear formula (approximately) linear? I don't have time to analyze it right now, but you may need to send b to 0 and c. to Inf. Compute a second-order Taylor approximation to your formula to find out.
Also, please set "trace=TRUE": Then the algorithm will tell you what it is trying to do with the parameter estimates.
You are persistent, Andrea: You will get an answer.
Best Wishes, Spencer Graves
Andrea Calandra wrote:
Sorry
I'm student in biomedical engineer and i have to solve this formula for immuno-assay. I need to design a calibration curve
But i don't understand How can i write this formula in R language: y = a + (c - a) /(1+ e[-b(x-m])
where x = ln(analyte dose + 1) y = the optical absorbance data a = the curves top asymptote b = the slope of the curve c = the curves bottom asymptote m = the curve X intercept
I have to calculate the parameters (a,b,c,m).After with X that i know i calculate the Y.
i try:
yeld.fit <- nls( y ~ a + (c.-a)/(1+exp(-b*(x-m))), data = yeld, start = list( a= 0, c.=2, b= 1, m=4 ), trace = TRUE )
where yeld is a data.frame x y 1 1 1 2 2 2 3 3 3 4 4 4 5 5 5
but give me an error: << exceeded number of itwerations>>
thank you Andrea
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