Description Usage Arguments Details Value Author(s) References Examples

`ogmix`

can be used to obtain the Mixed Regression 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 |

`R` |
is a |

`dpn` |
dispersion matrix of vector of disturbances of linear restricted model, |

`delt` |
values of |

`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 calculate the Ordinary Generalized Mixed Regression Estimator the prior information are required. Therefore those prior information should be mentioned within the function.

`ogmix`

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

P.Wijekoon, A.Dissanayake

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

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

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