Data driven smooth tests for composite hypotheses

Inglot, Tadeusz and Kallenberg, W.C.M. and Ledwina, Teresa (1997) Data driven smooth tests for composite hypotheses. Annals of Statistics, 25 (3). pp. 1222-1250. ISSN 0090-5364

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Abstract:	The classical problem of testing goodness-of-fit of a parametric family is reconsidered. A new test for this problem is proposed and investigated. The new test statistic is a combination of the smooth test statistic and Schwarz's selection rule. More precisely, as the sample size increases, an increasing family of exponential models describing departures from the null model is introduced and Schwarz's selection rule is presented to select among them. Schwarz's rule provides the "right" dimension given by the data, while the smooth test in the "right" dimension finishes the job. Theoretical properties of the selection rules are derived under null and alternative hypotheses. They imply consistency of data driven smooth tests for composite hypotheses at essentially any alternative.
Item Type:	Article
Copyright:	© 1997 Institute of Mathematical Statistics
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Statistics and Probability (SP)
Link to this item:	http://purl.utwente.nl/publications/62409
Official URL:	http://dx.doi.org/10.1214/aos/1069362746
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