eduzhai > Physical Sciences > Physics Sciences >

Robust Estimation of the Normal-Distribution Parameters by Use of Structural Partitioning-Perobls D Method

  • Save

... pages left unread,continue reading

Document pages: 15 pages

Abstract: Quite many authors have dealt with the estimation of the parameters of normal distribution on the basis of non-homogeneous sets: Hald A. 1949 [1], Arango-Castillo L. and Takahara G. 2018 [2]. All the robust methods are based on the assumption that the results affected by gross errors can be found to the left and or to the right of censoring, or truncated, points. However, as a rule, the (intrinsic) distribution of observations is complex (mixed) consisting of two or more distributions. Then the existing methods, such as ML, Huber’s, etc., yield enlarged estimates for the normal-distribution variance. By studying better estimates the present author has invented new method, called PEROBLS D, based on the Tukeyan mixed-distribution model in which both the contamination rate (percentage) and the parameters of both distributions, forming the mixed one, are estimated, and for the parameters of the basic normal distribution better estimates are obtained than by the existing methods.

Please select stars to rate!


0 comments Sign in to leave a comment.

    Data loading, please wait...