Description Usage Arguments Details Value Author(s) References Examples
This function can be used to find the Restricted Least Square Estimated values and corresponding scalar Mean Square Error (MSE) value.
1 |
formula |
in this section interested model should be given. This should be given as a |
r |
is a j by 1 matrix of linear restriction, r = Rβ + δ + ν. Values for |
R |
is a j by p of full row rank j ≤ p matrix of linear restriction, r = Rβ + δ + ν. Values for |
delt |
values of E(r) - Rβ and that should be given as either a |
data |
an optional data frame, list or environment containing the variables in the model. If not found in |
na.action |
if the dataset contain |
... |
currently disregarded. |
Since formula has an implied intercept term, use either y ~ x - 1
or y ~ 0 + x
to remove the intercept.
In order to find the results of Restricted Least Square Estimator, prior information should be specified.
rls
returns the Restricted Least Square Estimated values, standard error values, t statistic values,p value and corresponding scalar MSE value.
P.Wijekoon, A.Dissanayake
Hubert, M.H. and Wijekoon, P. (2006) Improvement of the Liu estimator in the linear regression medel, Chapter (4-8)
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