New graphical methods and test statistics for testing composite normality

Artikel

Several graphical methods for testing univariate composite normality from an i.i.d. sample are presented. They are endowed with correct simultaneous error bounds and yield size-correct tests. As all are based on the empirical CDF, they are also consistent for all alternatives. For one test, called the modified stabilized probability test, or MSP, a highly simplified computational method is derived, which delivers the test statistic and also a highly accurate p-value approximation, essentially instantaneously. The MSP test is demonstrated to have higher power against asymmetric alternatives than the well-known and powerful Jarque-Bera test. A further size-correct test, based on combining two test statistics, is shown to have yet higher power. The methodology employed is fully general and can be applied to any i.i.d. univariate continuous distribution setting.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 3 ; Year: 2015 ; Issue: 3 ; Pages: 532-560 ; Basel: MDPI

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Model Evaluation, Validation, and Selection
• Subject: calibration for simultaneity ; combined tests ; distribution testing ; P-P plot ; Q-Q plot ; simultaneous null bands

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Paolella, Marc S.
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2015

Further information

• DOI: doi:10.3390/econometrics3030532
• Handle: http://hdl.handle.net/10419/171838
• Last update: 10.03.2025, 11:44 AM CET