A general algorithm fob,univariate and multivariate goodness of pit tests based on graphical representation

This paper presents a general algorithm tor assessing the distributional assumptions. Empirical distributions of the corresponding test statistics are obtained and examples are given to illustrate various applications of the proposed test. By using the squared radii and angles, it is shown that the problem of assessing multivariate normality can be reduced to that of testing for a univariate distribution. A limited comparison is made to investigate the power of the proposed test. This work was supported in part by the National Science Foundation under Grant NO.G88135. Support from the Computer Applications ami Software Engineering (CASE) Center of Syracuse University is also gratefully acknowledged