Core Concepts¶
Many times we want to fit a parameterized function to data.
For example, suppose that we have an array of data
y[n] that we want to fit as a linear function of the variables
x[n],
where the n-th element of each array.
That is, we want to find the slope a and the y-intercept b
such that
a*x[n] + b is as close as possible to y[n].
We define “as close as possible” to mean that the
sum of the squared difference between y[n] and
a*x[n] + b is as small as possible.
Fitting is the process of finding parameters a and b
that make the fitting function as close as possible to the observational
data.
Thus, to perform fitting, we must specify:
the fitting function;
the parameters of the function that are to be adjusted;
observational data;