Displaying similar documents to “Model selection for (auto-)regression with dependent data”

Model selection for regression on a random design

Yannick Baraud (2010)

ESAIM: Probability and Statistics

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We consider the problem of estimating an unknown regression function when the design is random with values in ℝ k . Our estimation procedure is based on model selection and does not rely on any prior information on the target function. We start with a collection of linear functional spaces and build, on a data selected space among this collection, the least-squares estimator. We study the performance of an estimator which is obtained by modifying this least-squares estimator on...

Goodness of fit test for isotonic regression

Cécile Durot, Anne-Sophie Tocquet (2010)

ESAIM: Probability and Statistics

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We consider the problem of hypothesis testing within a monotone regression model. We propose a new test of the hypothesis : “” against the composite alternative : “” under the assumption that the true regression function is decreasing. The test statistic is based on the 𝕃 1 -distance between the isotonic estimator of and the function , since it is known that a properly centered and normalized version of this distance is asymptotically...