多维广义线性模型拟极大似然估计的弱相合性

Weak Consistency of Quasi-Maximum Likelihood Estimates in Multivariate Generalized Linear Models

  • 摘要: 本文考虑多维广义线性模型的拟似然方程\tsm^n_i=1X_i(y_i-\mu(X_i'\xb))=0, 在一定条件下证明了此方程的解\wh\xb_n渐近存在, 并得到了其收敛速度, 即\wh\xb_n-\xb_0=O_p(\underline\xl_n^-1/2), 其中\xb_0为参数\xb的真值, \underline\xl_n是方阵S_n=\tsm^n_i=1X_iX_i'的最小特征值。

     

    Abstract: In this paper, we study quasi-likelihood equation \tsm_i=1^nX_i(y_i-\mu(X_i'\beta))=0 for multivariate generalized linear models (GLMs). Under mild conditions, we prove the asymptotic existence of the solution \wh\beta_n to the above equation and present its convergence rate, that is \wh\beta_n-\beta_0=O_p(\underline\lambda_n^-1/2), where \beta_0 is the true value of parameter \beta and \underline\lambda_n denotes the smallest eigenvalue of the matrix S_n=\tsm_i=1^nX_iX_i'.

     

/

返回文章
返回