Data-driven efficient score tests for deconvolution problems

Details Data-driven efficient score tests for deconvolution problems Data-driven efficient score tests for deconvolution problems

2007-07-05

arxiv.org/abs/0707.0861v1

Mathematics

Statistics Theory

Scientific paper

10.1088/0266-5611/24/2/025028

We consider testing statistical hypotheses about densities of signals in deconvolution models. A new approach to this problem is proposed. We constructed score tests for the deconvolution with the known noise density and efficient score tests for the case of unknown density. The tests are incorporated with model selection rules to choose reasonable model dimensions automatically by the data. Consistency of the tests is proved.

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