1.
Exploratory Data Analysis
1.3.
EDA Techniques
1.3.6.
Probability Distributions
1.3.6.5.
Estimating the Parameters of a Distribution

Least Squares

Nonlinear least squares
provides an alternative to maximum likelihood.

Advantages

The advantages of this method are:
 Nonlinear least squares software may be available in many
statistical software packages that do not support maximum
likelihood estimates.
 It can be applied more generally than maximum likelihood.
That is, if your software provides nonlinear fitting and
it has the ability to specify the probability function you
are interested in, then you can generate least squares
estimates for that distribution. This will allow you to obtain
reasonable estimates for distributions even if the software
does not provide maximum likelihood estimates.

Disadvantages

The disadvantages of this method are:
 It is not readily applicable to censored data.
 It is generally considered to have less desirable optimality
properties than maximum likelihood.
 It can be quite sensitive to the choice of starting values.

Software

Nonlinear least squares fitting is available in many general
purpose statistical software programs.
