![]() We describe now in a more precise way how the Least Squares method is implemented, and, under a Population Regression Function that incorporates assumptions (A.1) to (A.6), which are its statistical properties. 4.1 The Least Squares Estimators as Random Variables To repeat an important passage from Chapter 3, when the formulas for b1 and b2, given in Equation (3.3.8), are taken to be rules that are used whatever the sample data turn out to be, then b1 and b2 are random variables since their values depend on the random variable y whose values are not known until the sample is collected. It extends Thm 3.1 of Basawa and … Some simulation results are also presented to illustrate the behavior of FLSEs. Under mild assumptions, it is shown that the WLS estimators of PARMA models are strongly consistent and asymptotically normal. Properties of least squares estimators 1II1’1tors”0.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |