It is difficult to study the mean value properties of the higher-Kloosterman sums S（m,n,q;k） for any positive integer k.In this paper,the fourth power mean of this exponential sums is studied by combining congruence...It is difficult to study the mean value properties of the higher-Kloosterman sums S（m,n,q;k） for any positive integer k.In this paper,the fourth power mean of this exponential sums is studied by combining congruence theorey with the analytic method,and an interesting asymptotic formula for it is obtained.The new result is an important generalization and improvement of the previous.展开更多
For the Generalized Linear Model (GLM), under some conditions including that the specification of the expectation is correct, it is shown that the Quasi Maximum Likelihood Estimate (QMLE) of the parameter-vector is as...For the Generalized Linear Model (GLM), under some conditions including that the specification of the expectation is correct, it is shown that the Quasi Maximum Likelihood Estimate (QMLE) of the parameter-vector is asymptotic normal. It is also shown that the asymptotic covariance matrix of the QMLE reaches its minimum (in the positive-definte sense) in case that the specification of the covariance matrix is correct.展开更多
基金Project supported by the Special Foundation for Excellent Young Teacher to Scientific Research (Grant No.2007GQS0142)the Innovation Foundation of Shanghai University
文摘It is difficult to study the mean value properties of the higher-Kloosterman sums S（m,n,q;k） for any positive integer k.In this paper,the fourth power mean of this exponential sums is studied by combining congruence theorey with the analytic method,and an interesting asymptotic formula for it is obtained.The new result is an important generalization and improvement of the previous.
基金Project supported by the National Natural Science Foundation of China.
文摘For the Generalized Linear Model (GLM), under some conditions including that the specification of the expectation is correct, it is shown that the Quasi Maximum Likelihood Estimate (QMLE) of the parameter-vector is asymptotic normal. It is also shown that the asymptotic covariance matrix of the QMLE reaches its minimum (in the positive-definte sense) in case that the specification of the covariance matrix is correct.
