the article correctly points out that 3 parameters need to be estimated but then jumps directly to modeling those 3 parameters with 3 points and that that will always be wrong.
that’s not the right intuition. you could model a logistic curve with just 3 points if the error in those measurements tended toward infinity. the further apart the points are, the less tight the error bars need to be.
the problem with real-world modeling/curve-fitting is that measurements are super noisy and the errors in them are significant.
that’s not the right intuition. you could model a logistic curve with just 3 points if the error in those measurements tended toward infinity. the further apart the points are, the less tight the error bars need to be.
the problem with real-world modeling/curve-fitting is that measurements are super noisy and the errors in them are significant.