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  • Search: subject:"Mean squared error minimizer"
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Year of publication
Subject
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Maximum likelihood 3 Mean squared error minimizer 3 Penalized splines 3 Smoothing splines 3 Estimation theory 1 Nichtparametrisches Verfahren 1 Nonparametric statistics 1 Regression analysis 1 Regressionsanalyse 1 Schätztheorie 1 Time series analysis 1 Zeitreihenanalyse 1
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Online availability
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Free 3
Type of publication
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Book / Working Paper 3
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1
Language
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English 3
Author
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Krivobokova, Tatyana 3
Institution
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Courant Research Centre PEG 1
Published in...
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Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 1 Discussion Papers 1 Discussion papers / Courant Research Centre "Poverty, Equity and Growth in Developing and Transition Countries: Statistical Methods and Empirical Analysis" 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
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Smoothing parameter selection in two frameworks for penalized splines
Krivobokova, Tatyana - 2011
There are two popular smoothing parameter selection methods for spline smoothing. First, criteria that approximate the average mean squared error of the estimator (e.g. generalized cross validation) are widely used. Alternatively, the maximum likelihood paradigm can be employed under the...
Persistent link: https://www.econbiz.de/10010329897
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Cover Image
Smoothing parameter selection in two frameworks for penalized splines
Krivobokova, Tatyana - Courant Research Centre PEG - 2011
There are two popular smoothing parameter selection methods for spline smoothing. First, criteria that approximate the average mean squared error of the estimator (e.g. generalized cross validation) are widely used. Alternatively, the maximum likelihood paradigm can be employed under the...
Persistent link: https://www.econbiz.de/10009209706
Saved in:
Cover Image
Smoothing parameter selection in two frameworks for penalized splines
Krivobokova, Tatyana - 2011 - last revision Oct. 2012
There are two popular smoothing parameter selection methods for spline smoothing. First, criteria that approximate the average mean squared error of the estimator (e.g. generalized cross validation) are widely used. Alternatively, the maximum likelihood paradigm can be employed under the...
Persistent link: https://www.econbiz.de/10010349176
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