An Improved Goodness-of-Fit Statistic for Sparse Multinomials
提出一种针对稀疏多项分布的新拟合优度统计量，基于Simonoff的最大后验估计概率，通过计算机模拟显示在备择分布平滑时比标准检验功效显著提升。
Abstract A new goodness-of-fit statistic for sparse multinomials is proposed. It is assumed that the null distribution exhibits smoothness. The test statistic is based on the maximum posterior estimator probability estimates of Simonoff (1983). Computer simulations are used to estimate the null distribution, significance levels, and the power function of the test. It is shown that power of the test is a great improvement over that of the standard tests if the alternative distribution exhibits smoothness. Key Words: Chi-squared statisticSmoothingMaximum penalized likelihoodComputer simulations