Data-Driven Smooth Tests for a Location-Scale Family Revisited
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A new data-driven, smooth goodness of test for a location-scale family is proposed and studied. The new test statistic is a combination of an efficient score statistic and an appropriate selection rule. Some examples are presented and by using extensive simulations the test is shown to have desirable properties.
Key-wordsEfficient score statistic Goodness-of-fit test Model selection Schwarz’s rule Test for extreme value distribution Test for normality
AMS Subject Classification62G10 62G20
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- Greenwood, J., Landwehr, J., Matalas, N., 1979. Probability weighted moments: definition and relation to parameters of several distributions expressible in inverse form. Water Resour. Res., 15, 1049–1054.Google Scholar
- Inglot, T., Kallenberg, W., Ledwina, T., 1994. On selection rules with an application to goodness-of-fit for composite hypotheses. Memorandum 1242. University of Twente, Faculty of Applied Mathematics.Google Scholar
- Inglot, T., Ledwina, T., 2001. Asymptotic optimality of data driven smooth tests for location-scale family. Sankhyā Ser. A, 60,41-71.Google Scholar
- Inglot, T., Ledwina, T., 2006b. Data-driven score tests for homoscedastic linear regression model: the construction and simulations. In M. Hušková, M. Janžura (eds.), Prague Stochastics 2006. Proceedings, 124–137. Matfyzpress, Prague.Google Scholar
- Javitz, H., 1975. Generalized smooth tests of goodness of fit, independence and equality of distributions. Ph.D. thesis, University of California., Berkeley, USA.Google Scholar
- Landwehr, J., Matalas, N., 1979. Probability weighted moments compared with some traditional techniques in estimating Gumbel parameters and quantiles. Water Resour. Res., 15, 1055–1064.Google Scholar
- Le Cam, L., Lehmann, E., 1974. J. Neyman — on the occasion of his 80th birthday. Ann. Statist., 2, vii-xiii.Google Scholar
- Neyman, J., 1959. Optimal asymptotic tests of composite statistical hypotheses. In U. Grenander (ed.), Probability and Statistics, Harald Cramér Volume, 212–234. Wiley, New York.Google Scholar