The Rate of Convergence of the Least Square Estimator in a Nonlinear Regression with φ-mixing Errors

For nonlinear model X_n＝y_n（θ）＋ε_n, we obtain the a.s. convergence rate of the LS estimatorθn, provided that {ε_n} is an φ-mixing errors with Eε_i=θ, sup_iE|ε_i|^t＜∞（for some t＞2）, $$\sum_i^{\infty} \Phi^{1 / 2}(i)<\infty$$ and other suitabe conditions, which generalized and improved Prakasa Rao’sresult （J. Mult. Anal. 14（1984）,315-322）.