Curve Fitter

A fork of ImageJ CurveFitter without any java.awt or GUI dependencies.

Import this library into an Android (i.e. Java) project to use various regression algorithms, such as:

• Straight Line: y = a + bx
• 2nd Degree Polynomial: y = a + bx + cx^2
• 3rd Degree Polynomial: y = a + bx + cx^2 + dx^3
• 4th Degree Polynomial: y = a + bx + cx^2 + dx^3 + ex^4
• Exponential: y = a * exp(bx)
• Power: y = a * x^b
• Log: y = a * ln(bx)
• Rodbard: y = d + (a - d)/(1 + (x/c)^b)
• Gamma Variate: y = b * (x - a)^c * exp(-(x - a)/d)
• Log with offset: y = a + b * ln(x - c)
• Rodbard (NIH Image): x = d + (a - d)/(1 + (y/c)^b), or y = c * ((x - a)/(d - x))^(1/b)]
• Exponential with Offset: y = a * exp(-bx) + c
• Gaussian: y = a + (b - a) * exp(-(x - c)*(x - c)/(2 * d * d))
• Exponential Recovery: y = a * (1 - exp(-b * x)) + c
• Inverse Rodbard: y = c * ((x - a)/(d - x))^(1/b)
• Exponential (linear regression): y = a * exp(bx)
• Power (linear regression): y = a * x^b
• 5th Degree Polynomial: y = a + bx + cx^2 + dx^3 + ex^4 + fx^5
• 6th Degree Polynomial: y = a + bx + cx^2 + dx^3 + ex^4 + fx^5 + gx^6
• 7th Degree Polynomial: y = a + bx + cx^2 + dx^3 + ex^4 + fx^5 + gx^6 + hx^7
• 8th Degree Polynomial: y = a + bx + cx^2 + dx^3 + ex^4 + fx^5 + gx^6 + hx^7 + ix^8
• Gaussian (no offset): y = a * exp(-(x - b)*(x - b)/(2 * c * c)))
• Exponential Recovery (no offset): y = a * (1 - exp(-b * x))
• Chapman-Richards: y = a * (1 - exp(-b * x))^c

Usage

double[] xs = {1, 2, 3, 4, 5, 6};
double[] ys = {-2, 0, 6, 16, 30, 48};
CurveFitter curveFitter = new CurveFitter(xs, ys);
curveFitter.doFit(CurveFitter.POLY2);
double[] params = curveFitter.getParams();

double a = params[0];
double b = params[1];
double c = params[2];
// y = a + bx + cx^2