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Register a new userData-driven efficient score tests for deconvolution problems
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Added by
Mikhail Langovoy
Publication date
2007
fields
Mathematical Statistics
and research's language is
English
Authors
Mikhail Langovoy
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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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