This paper deals with the development of a unified theory for identification of parameters of a linear, discrete time system which is described by either causal or noncausal ARMA model. We study in detail the convergence properties of a parameter identification algorithm called least squares with covariance modification (LSCOM) and show how the convergence properties of a number of other related algorithms can be derived as special cases of the LSCOM algorithm.