Estimation of a standard measuring error by repeated measurements and sortings

In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy y i | (x i , t i) ∼ F (•, µ i) with µ i = H η(t i) + x t i β and H a known link function, we want to test H 0 : η(t) = α + γt against H 1 : η is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasilikelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained.

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Estimation of a standard measuring error by repeated measurements and sortings

Cited by 3 publications

References 7 publications

Statistical models and learning algorithms for ordinal regression problems

Statistical models and learning algorithms for ordinal regression problems

Some statistical aspects of binary measuring systems

Testing in generalized partially linear models: A robust approach

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