
Jun 26th, 2002, 12:26 PM
#1
Thread Starter
Junior Member
Curve Fitting for 4 parameter logistic equation
I am new to this math forum, and I hope that this is an appropriate place to post this question...
I need to fit data to the "4 parameter logisitic equation" for biological relationships. Essentially the equation is the following:
y = ((AD) / (1+ ((x/C)^B))) + D
Basically, I'll have an equally sized array of x and y values that are used to solve for variables A,B,C, and D. Right now I need to use one function from a statistical package to solve for this. I'd like to reproduce this function in the language that I am confortable with (VBA), but don't have a clue about how to approach the math! Does anyone know how to do this?!

Jun 26th, 2002, 06:12 PM
#2
pathfinder

Jun 27th, 2002, 01:55 PM
#3
Hyperactive Member
I think you could use the Solver feature in Excel to find A, B, C & D for given x & y, although your post suggests you want/need to use statistical functions. Post back if we can help you with the Solver feature.
There are 10 types of people in the world  those that understand binary, and those that don't.

Jun 27th, 2002, 03:00 PM
#4
Thread Starter
Junior Member
Thanks NotLKH and David for your insight so far. I really appreciate the input. Ideally, I'd like to use pure VB or VBA code. The vendor for the package that I have been using so far said their nonlinear regression algorithm is based on the LevenbergMarquardt method in the publication Numerical Recipes in C (http://chemistry.about.com/gi/dynami...Fbookcpdf.html). Being a dummy in C, C++, and matrix algebra, it all looks like jibberish to me! Does anyone know how to apply the stated method for the model that I originally posted?! From the looks of it, this is starting to be a bear of a project!

Jun 27th, 2002, 10:18 PM
#5
pathfinder
How many {X, Y} Pairs would you have?

Jun 28th, 2002, 11:03 AM
#6
Thread Starter
Junior Member
Typically, I would have 18 {X,Y} pairs. The data is made up of triplicate observations at 6 input values. I hope this helps!
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