3. Least square method
• The method of least squares is about estimating
parameters by minimizing the squared error between
observed data and their expected values.
• The linear regression is the simple type of parametric
model.
• This model structure can be written as
Y(t) = ФT (t) Ɵ
Where,
Y(t) = Measurable Quantity
Ф(t) = n – Vector of known quantities
= [ -Y(t-1), -Y(t-2), …., -Y(t-na) u(t-1) …-u(t-nb)]T
Ɵ = n – Vector of unknown parameters.