Asymptotic Properties of Parameters for Linear Circular Functional Relationship Model

This study discusses the asymptotic properties of parameters for unreplicated linear circular functional relationship model. The model is formulated assuming both variables are circular, subject to errors and there is a linear relationship between them. The Maximum Likelihood Estimation (MLE) have been used to estimate the slope parameters ( 2), intercept ( ±) and error concentration parameters for both variables which are o and v, respectively. The Fisher information matrix have been derived and based on this we estimated the asymptotic covariance matrix of