empirical distribution;
Monte Carlo simulation;
normality test;
Q statistic;
D O I:
10.1080/02664760600995064
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
Zhang ( 1999) proposed a novel test statistic Q for testing normality based on the ratio of two unbiased standard deviation estimators, q1 and q2, for the true population standard deviation sigma. Mingoti & Neves ( 2003) discussed some properties of q1 and q2 and showed that the variance of q1 increases as the true population variance increases. In this paper, we show that the distribution of q1 is not normal. As a result, normality percentage points for Q are not appropriate. In this paper, percentage points of Q are obtained using simulations. Monte Carlo simulations are provided to evaluate the performance of the new method and Zhang's method.
机构:
Johannes Kepler Univ Linz, Dept Appl Stat, Linz, Austria
UC Santa Barbara, Kavli Inst Theoret Phys, Santa Barbara, CA USA
Univ Vet Med, Vienna Grad Sch Populat Genet, Vienna, AustriaJohannes Kepler Univ Linz, Dept Appl Stat, Linz, Austria
Futschik, Andreas
Taus, Thomas
论文数: 0引用数: 0
h-index: 0
机构:
Univ Vet Med, Vienna Grad Sch Populat Genet, Vienna, Austria
Univ Vet Med, Inst Populat Genet, Vienna, AustriaJohannes Kepler Univ Linz, Dept Appl Stat, Linz, Austria