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Samples NA dependent case , the least squares estimation of the regression coefficients of the linear regression model Strong Consistency of error density estimation strong , weak consistency , as well as non-parametric regression model regression the KERNEL estimated Consistency . Text includes the following two main parts : the first part : we get the the sample NA dependent linear regression model y_i = x'_iβ e_i , i = 1,2 , ... , n , the least squares estimation of the regression coefficients Strong Consistency prove the error estimates of weak consistency , strong consistency, and gives it the convergence rate . Part II: We studied a sample of NA - dependent , non- parametric regression model Y_i = g ( X_i ) ε_ii and = 1,2 , ... , n , the kernel estimator of the regression function strong , weak Consistency .
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