Regression rank scores in nonlinear models

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dc.creatorJurečková, Jana
dc.date2008-05-15
dc.date.accessioned2026-07-07T12:18:55Z
dc.date.available2026-07-07T12:18:55Z
dc.descriptionConsider the nonlinear regression model $Y_i=g({\bf x}_i,\boldmath $θ$)+e_i,\quad i=1,...,n$(1) with ${\bf x}_i\in \mathbb{R}^k,$ $\boldmathθ=(θ_0,θ_1,...,θ_p)^{\prime}\in \boldmath $Θ$$ (compact in $\mathbb{R}^{p+1}$), where $g({\bf x},\boldmath $θ$)=θ_0+\tilde{g}({\bf x},θ_1,...,θ_p)$ is continuous, twice differentiable in $\boldmath $θ$$ and monotone in components of $\boldmath $θ$$. Following Gutenbrunner and Jurečková (1992) and Jurečková and Procházka (1994), we introduce regression rank scores for model (1), and prove their asymptotic properties under some regularity conditions. As an application, we propose some tests in nonlinear regression models with nuisance parameters.
dc.descriptionPublished in at http://dx.doi.org/10.1214/193940307000000121 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0805.2300
dc.identifierhttp://arxiv.org/abs/0805.2300
dc.identifierIMS Collections 2008, Vol. 1, 173-183
dc.identifierdoi:10.1214/193940307000000121
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212580
dc.subjectStatistics Theory
dc.subject62G08 (Primary) 62J02 (Secondary)
dc.titleRegression rank scores in nonlinear models
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