An Inconsistent Maximum Likelihood Estimate
给出一个在三角分布与均匀分布之间的连续参数化分布族，其最大似然估计总是收敛到参数值1，无论真实参数为何，并给出了满足Cramér条件的修正版本。
Abstract An example is given of a family of distributions on [— 1, 1] with a continuous one-dimensional parameterization that joins the triangular distribution (when Θ = 0) to the uniform (when Θ = 1), for which the maximum likelihood estimates exist and converge strongly to Θ = 1 as the sample size tends to infinity, whatever be the true value of the parameter. A modification that satisfies Cramér's conditions is also given.