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On the estimation of a monotone conditional variance in nonparametric regression
Dette, Holger; Pilz, Kay F. - 2004
A monotone estimate of the conditional variance function in a heteroscedastic, nonpara- metric regression model is …
Persistent link: https://www.econbiz.de/10010296626
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Shape constrained estimators in inverse regression models with convolution-type operator
Birke, Melanie; Bissantz, Nicolai - 2007
In this paper we are concerned with shape restricted estimation in inverse regression problems with convolution …) unconstrained estimate of the unknown regression function. An advantage of our approach is that it is not necessary that prior shape … information is known to be valid on the complete domain of the regression function. Instead, it is sufficient if it holds on some …
Persistent link: https://www.econbiz.de/10010298216
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More on confidence intervals for partially identified parameters
Stoye, Jörg - 2008
This paper extends Imbens and Manski's (2004) analysis of confidence intervals for interval identified parameters. For their final result, Imbens and Manski implicitly assume superefficient estimation of a nuisance parameter. This appears to have gone unnoticed before, and it limits the result's...
Persistent link: https://www.econbiz.de/10010288438
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Estimating a convex function in nonparametric regression
Dette, Holger; Birke, Melanie - 2005
A new nonparametric estimate of a convex regression function is proposed and its stochastic properties are studied. The … method starts with an unconstrained estimate of the derivative of the regression function, which is firstly isotonized and … equivalent to the initial unconstrained estimate if the regression function is in fact convex. If convexity is not present the …
Persistent link: https://www.econbiz.de/10010296683
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Imposing and testing curvature conditions on a Box-Cox function
Koebel, Bertrand M.; Falk, Martin; Laisney, François - 2000
We present a new method for imposing and testing concavity of a cost function using asymptotic least squares, which can easily be implemented even for cost functions which are nonlinear in parameters. We provide an illustration on the basis of a (generalized) Box-Cox cost function with six...
Persistent link: https://www.econbiz.de/10010297734
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Confidence sets and non-parametric regression
Davies, P. Laurie; Kovac, Arne; Meise, Monika - 2007
Persistent link: https://www.econbiz.de/10010298196
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Optimal Convergence Rates in Nonparametric Regression with Fractional Time Series Errors
Feng, Yuanhua - 2002
Persistent link: https://www.econbiz.de/10010324049
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Modifying the double smoothing bandwidth selector in nonparametric regression
Beran, Jan; Feng, Yuanhua; Heiler, Siegfried - 2000
In this paper a modified double smoothing bandwidth selector, ^h MDS , based on a new criterion, which combines the plug-in and the double smoothing ideas, is proposed. A self-complete iterative double smoothing rule (^h_IDS ) is introduced as a pilot method. The asymptotic properties of both...
Persistent link: https://www.econbiz.de/10010324090
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Partial linear quantile regression and bootstrap confidence bands
Härdle, Wolfgang Karl; Ritov, Ya'acov; Song, Song - 2010
In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions …
Persistent link: https://www.econbiz.de/10010270724
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On rate optimality for ill-posed inverse problems in econometrics
Chen, Xiaohong; Reiß, Markus - 2007
nonparametric indirect regression (NPIR) and nonparametric instrumental variables (NPIV) regression models. We establish minimax …
Persistent link: https://www.econbiz.de/10010318567