论文检索

若干正态混合分布估计方法的比较AI 解读

Fisher's method of maximum likelihood breaks down when applied to the problem of estimating the five parameters of a mixture of two normal densities from a continuous random sample of size n. Two alternative methods, (i) moment estimates and (ii) multinomial maximum likelihood and niinimum x2 estimates obtained by grouping the underlying variable, are compared both for bias to n⊟θ1 and mean squared error to n⊟θ2 for a variety of mixed distributions. The methods do not differ…

二元两样本位置问题的 David–Fix 非参数检验AI 解读

Some large-sample properties of the three nonparametric tests of David and Fix for the two-sample bivariate location problem are given. In particular the Pitman A.R.E.s of the tests against some ‘normal-theory’ competitors are shown to be satisfactory in most cases for a number of ‘near-normal’ bivariate distributions. Their performances in some mixtures of bivariate normal distributions prove to be particularly convincing. A useful relationship between the three test…

双变量两样本位置问题的 David–Fix 非参数检验AI 解读

Some large-sample properties of the three nonparametric tests of David and Fix for the two-sample bivariate location problem are given. In particular the Pitman A.R.E.s of the tests against some ‘normal-theory’ competitors are shown to be satisfactory in most cases for a number of ‘near-normal’ bivariate distributions. Their performances in some mixtures of bivariate normal distributions prove to be particularly convincing. A useful relationship between the three test…

矩估计量的偏差与准确性AI 解读

A new method for finding the biases and covariances of moment estimators to order n−2 is outlined and compared with existing solutions. It is thought that the new approach is likely to be particularly useful for cases where moment estimation is complicated. The application of the method to mixtures of normal distributions is considered in some detail and some numerical results are included.

摘要暂缺

指数分布均值标准估计量对污染的稳健性AI 解读

The performances of the standard estimators of the mean of an exponential distribution are evaluated when this basic distribution is contaminated by another of the same type. Surprisingly, perhaps, it is found that the sample mean is asymptotically fully efficient for the mean of a mixture. For small samples, on the other hand, a comparison of the two standard statistics with the appropriate optimal linear statistics in terms of the mean squared error and bias shows that for…