Hi,
May be someone can help me with this problem.
Given the follow function: y = 10 ^ ((x + 82) / (-10 * A))
I would like to found the A value witch curve fit better for a set of x,y
values, usually the set is about 20 to 25 x,y values.
I use the CurveFitter class and the ParametricUnivariateFunction
ParametricUnivariateFunction function = new ParametricUnivariateFunction()
{
@Override
public double[] gradient(double x, double[] params) {
(????? comment)
}
@Override
public double value(double x, double[] params) {
double a = params[0];
return Math.pow(10, ((x + 82) /
(
-10 *
a
)
));
}
};
LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
CurveFitter<ParametricUnivariateFunction> fitter = new
CurveFitter<ParametricUnivariateFunction>(optimizer);
double[] x = {
-82
,
-85
,
-89
};
double[] y = {
1
,
1.4
,
2
};
for (int i = 0; i < x.length; i++)
fitter.addObservedPoint(x[i], y[i]);
double[] result = fitter.fit(function, new double[] { 1, 10 });
A. Is this the best way to solve the problem or there's another better
way?
B. What do we need to write on the gradient area (????? comment) ?
Any help will be more then welcome.
Many thanks !!
