Stochastic Expansions and Asymptotic Approximations
研究了计量经济估计量或检验统计量的随机展开，其前几项的分布函数能提供比正态或卡方逼近误差更小的渐近逼近，从而验证了Nagar型矩比较和Edgeworth逼近等精细渐近方法的有效性。
Under general conditions the distribution function of the first few terms in a stochastic expansion of an econometric estimator or test statistic provides an asymptotic approximation to the distribution function of the original estimator or test statistic with an error of order less than that of the limiting normal or chi-square approximation. This can be used to establish the validity of several refined asymptotic methods, including the comparison of Nagar-type moments and the use of formal Edgeworth or Edgeworth-type approximations.