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Confidence bands for inverse regression models with application to gel electrophoresis
Birke, Melanie; Bissantz, Nicolai; Holzmann, Hajo - Institut für Wirtschafts- und Sozialstatistik, … - 2008
We construct uniform confidence bands for the regression function in inverse, homoscedastic regression models with convolution-type operators. Here, the convolution is between two non-periodic functions on the whole real line rather than between two period functions on a compact interval, since...
Persistent link: https://www.econbiz.de/10009216879
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Bandwidth selection for nonparametric regression with errors-in-variables
Dong, Hao; Otsu, Taisuke; Taylor, Luke - In: Econometric reviews 42 (2023) 4, pp. 393-419
Persistent link: https://www.econbiz.de/10014305525
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Nonparametric estimation with aggregated data
Linton, Oliver; Whang, Yoon-Jae - London School of Economics (LSE) - 2000
We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intra-family component but require that observations from different families be in dependent. We establish consistency and asymptotic...
Persistent link: https://www.econbiz.de/10010928627
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A unified approach to solve ill-posed inverse problems in econometrics
JOHANNES, Jan; VAN BELLEGHEM, Sébastien; VANHEMS, Anne - Center for Operations Research and Econometrics (CORE), … - 2007
function fromdata contaminated by a noise whose distribution is unknown (blind deconvolution) and the nonparametric …
Persistent link: https://www.econbiz.de/10005008287
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Nonparametric Estimation with Aggregated Data
Linton, Oliver; Whang, Yoon-Jae - Suntory and Toyota International Centres for Economics … - 2000
We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intra-family component but require that observations from different families be in dependent. We establish consistency and asymptotic...
Persistent link: https://www.econbiz.de/10005797505
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Ill-posed inverse problems in economics
Horowitz, Joel - 2013
A parameter of an econometric model is identified if there is a one-to-one or many-to-one mapping from the population distribution of the available data to the parameter. Often, this mapping is obtained by inverting a mapping from the parameter to the population distribution. If the inverse...
Persistent link: https://www.econbiz.de/10009778441
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Nonparametric estimation of additive model with errors-in-variables
Dong, Hao; Otsu, Taisuke - 2018
Persistent link: https://www.econbiz.de/10012491601
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Nonparametric estimation of the density of a change-point
Carrasco, Marine; Peltier, Hugo - 2024
Persistent link: https://www.econbiz.de/10014478827
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Density Deconvolution with Replicate Measurements and Auxiliary Data
McIntyre, Julie P. - 2003
We present two deconvolution estimators for the density function of a random variable X that is measured with error … estimator generalizes the deconvolution estimator of Stefanski and Carroll (1990), with the measurement error variances … study and an example.The second is a semi-parametric deconvolution estimator that assumes the availability of a covariate …
Persistent link: https://www.econbiz.de/10009431272
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Ill-posed inverse problems in economics
Horowitz, Joel - 2013
A parameter of an econometric model is identified if there is a one-to-one or many-to-one mapping from the population distribution of the available data to the parameter. Often, this mapping is obtained by inverting a mapping from the parameter to the population distribution. If the inverse...
Persistent link: https://www.econbiz.de/10010318682