Mathematical Sciences
en
research_article
https://scigraph.springernature.com/explorer/license/
A general goodness-of-fit test for scale-parameter families of distributions is introduced, which is based on quotients of expected sample minima. The test is independent of the mean of the distribution, and, in applications to testing for exponentiality of data, compares favorably to other goodness-of-fit tests for exponentiality based on the empirical distribution function, regression methods and correlation statistics. The new minimal-moment method uses ratios of easily-calculated, unbiased, strongly consistent U-statistics, and the general technique can be used to test many standard composite null hypotheses such as exponentiality, normality or uniformity (as well as simple null hypotheses).
2001-09
543-551
Extreme-Value Moment Goodness-of-Fit Tests
false
2001-09-01
articles
http://link.springer.com/10.1023/A:1014673230617
2019-04-10T17:30
Statistics
pub.1035833890
dimensions_id
Perez-Abreu
Victor
Centro de InvestigacĂon en MatemĂˇticas, Gto 36000, Guanajuato, Mexico, e-mail
Mathematics Research Center
Springer Nature - SN SciGraph project
readcube_id
aab33d93fc13903bdf539cccc5824e1578245c6df0a241ac8b09bea941a0fe81
Theodore P.
Hill
doi
10.1023/a:1014673230617
Georgia Institute of Technology
School of Mathematics, Georgia Institute of Technology, 30332-0160, Atlanta, GA, USA, e-mail
Annals of the Institute of Statistical Mathematics
1572-9052
0020-3157
3
53