A new goodness of fit test for normal distribution based on Stein's characterization

2020/01/22 by Kattumannil, Sudheesh
#62G10 #62G20 #FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.2001.07932

Abstract

In this paper, we develop a simple non-parametric test for testing normal distribution based on the distance between empirical zero-bias transformation and empirical distribution. The asymptotic properties of the test statistic are studied. The finite sample performance of the proposed test is evaluated through a Monte Carlo simulation study. The power of our test is compared with several other tests for normality. We illustrate the test procedure using two real data sets. We also develop a jackknife empirical likelihood ratio test for standard normal distribution.

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