Parameter Estimations in Linear Regression Models with AR(2) Errors in Which the Parameters Have a Special Relationship

nt t t t t , , 2 , 1 , 2 2 1 1 � = + + = − − e μ φ μ φ μ in which the parameters have a special relationship 2 1 2 φ φ = . For the properties of variance-covariance matrix Σ , This kind of models are transformed into the standard linear regression models without autocorrelation errors and apply the method of cycle generalized least squares (CGLS) to estimate parameters. Simulation results show that efficiency of CGLS method is superior over the method of generalized least squares (GLS) under mean square error criterion.