# mixe: Ordinary Mixed Regression Estimator In lrmest: Different Types of Estimators to Deal with Multicollinearity

## Description

`mixe` can be used to obtain the Mixed Regression Estimated values and corresponding scalar Mean Square Error (MSE) value.

## Usage

 `1` ```mixe(formula, r, R, dpn, 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’. `dpn` dispersion matrix of vector of disturbances of linear restricted model, r = Rβ + δ + ν. Values for `dpn` should be given as either a `vector` (only the diagonal elements) 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 calculate the Mixed Regression Estimator the prior information are required. Therefore those prior information should be mentioned within the function.

## Value

`mixe` returns the Mixed Regression Estimated values, standard error values, t statistic values,p value and corresponding scalar MSE value.

## Author(s)

P.Wijekoon, A.Dissanayake

## References

Theil, H. and Goldberger, A.S. (1961) On pure and mixed statistical estimation in economics in International Economic review, volume 2, pp. 65–78

## 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) dpn<-c(0.0439,0.0029,0.0325) delt<-c(0,0,0) mixe(Y~X1+X2+X3+X4-1,r,R,dpn,delt,data=pcd) # Model without the intercept is considered. ```

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