This paper provides a general method for constructing generalized p-value via the fiducial inference.Furthermore,the power properties of the generalized test are discussed.As illustrations, the two-parameter exponential distribution and unbalanced two-fold nested design are researched.It is shown that the resulting generalized p-values are of good frequency property.
Xin-min LI~(1+) Xing-zhong XU~2 Guo-ying LI~3 1 Institute of Applied Mathematics,Shandong University of Technology,Zibo 255049,China
In practice, the unknown parameters are often restricted. This paper provides a general method for constructing the fiducial intervals of the restricted parameters. Applying the general method, the fiducial intervals are constructed for the location (scale)parameters and the difference (ratio) of two locations (scales) in a location (scale) family of distributions. The frequency properties of these intervals are verified. For a variance components model, the fiducial intervals for the three parameters of common interest are obtained. Their frequency properties are investigated theoretically and computationally.
LI Xinmin, LI Guoying & XU Xingzhong College of Mathematics and Information Sciences, Shandong University of Technology, Zibo 255049, China
In this paper, the interval estimation and hypothesis testing of the mixing proportion in mixture distributions are considered. A statistical inferential method is proposed which is inspired by the generalized p-values and generalized pivotal quantity. In some situations, the true levels of the tests given in the paper are equal to nominal levels, and the true coverage of the interval estimation or confidence bounds is also equal to nominal one. In other situations, under mild conditions, the tests are consistent and the coverage of the interval estimations or the confidence bounds is asymptotically equal to nominal coverage. Meanwhile, some simulations are performed which show that our method is satisfactory.
In this paper a family, called the pivotal family, of distributions is considered.A pivotal family is determined by a generalized pivotal model. Analytical results show that a great many parametric families of distributions are pivotal. In a pivotal family of distributions a general method of deriving fiducial distributions of parameters is proposed. In the method a fiducial model plays an important role. A fiducial model is a function of a random variable with a known distribution, called the pivotal random element, when the observation of a statistic is given.The method of this paper includes some other methods of deriving fiducial distributions. Specially the first fiducial distribution given by Fisher can be derived by the method. For the monotone likelihood ratio family of distributions, which is a pivotal family, the fiducial distributions have a frequentist property in the Neyman-Pearson view. Fiducial distributions of regular parametric functions also have the above frequentist property. Some advantages of the fiducial inference are exhibited in four applications of the fiducial distribution. Many examples are given, in which the fiducial distributions cannot be derived by the existing methods.
XU Xingzhong & LI Guoying Department of Mathematics, Beijing Institute of Technology, Beijing 100081, China
