# ogrls: Ordinary Generalized Restricted Least Square Estimator In lrmest: Different Types of Estimators to Deal with Multicollinearity

## Description

This function can be used to find the Ordinary Generalized Restricted Least Square Estimated values and corresponding scalar Mean Square Error (MSE) value.

## Usage

 `1` ```ogrls(formula, r, R, delt, data, na.action, ...) ```

## Arguments

 `formula` in this section interested model should be given. This should be given as a `formula`. `r` is a j by 1 matrix of linear restriction, r = Rβ + δ + ν. Values for `r` should be given as either a `vector` or a `matrix`. See ‘Examples’. `R` is a j by p of full row rank j ≤ p matrix of linear restriction, r = Rβ + δ + ν. Values for `R` should be given as either a `vector` or a `matrix`. See ‘Examples’. `delt` values of E(r) - Rβ and that should be given as either a `vector` or a `matrix`. See ‘Examples’. `data` an optional data frame, list or environment containing the variables in the model. If not found in `data`, the variables are taken from `environment(formula)`, typically the environment from which the function is called. `na.action` if the dataset contain `NA` values, then `na.action` indicate what should happen to those `NA` values. `...` currently disregarded.

## Details

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 Ordinary Generalized Restricted Least Square Estimator, prior information should be specified.

## Value

`ogrls` returns the Ordinary Generalized Restricted Least Square Estimated values, standard error values, t statistic values,p value and corresponding scalar MSE value.

## Author(s)

P.Wijekoon, A.Dissanayake

## References

Arumairajan, S. and Wijekoon, P. (2015) ] Optimal Generalized Biased Estimator in Linear Regression Model in Open Journal of Statistics, pp. 403–411

Hubert, M.H. and Wijekoon, P. (2006) Improvement of the Liu estimator in the linear regression medel, Chapter (4-8)

## Examples

 ```1 2 3 4 5 6 7``` ```## Portland cement data set is used. data(pcd) r<-c(2.1930,1.1533,0.75850) R<-c(1,0,0,0,0,1,0,0,0,0,1,0) delt<-c(0,0,0) ogrls(Y~X1+X2+X3+X4-1,r,R,delt,data=pcd) # Model without the intercept is considered. ```

lrmest documentation built on May 29, 2017, 9:02 a.m.