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~person:"Rakotomarolahy, Patrick"
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Search: subject:"asymptotic normality"
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economic indicators
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Multivariate k-nearest neighbor
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asymptotic normality
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asymptotic normality of the regression
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Rakotomarolahy, Patrick
Hallin, Marc
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Paindaveine, Davy
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Koopman, Siem Jan
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Nielsen, Morten Ørregaard
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Centre d'Économie de la Sorbonne, Université Paris 1 (Panthéon-Sorbonne)
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Alternative methods for forecasting GDP
Guegan, Dominique
;
Rakotomarolahy, Patrick
-
HAL
-
2010
nearest neighbor method. We prove also the
asymptotic
normality
of the multivariate k-nearest neighbor regression estimator …
Persistent link: https://www.econbiz.de/10010603668
Saved in:
2
Alternative methods for forecasting GDP
Guegan, Dominique
;
Rakotomarolahy, Patrick
-
HAL
-
2010
nearest neighbor method. We prove also the
asymptotic
normality
of the multivariate k-nearest neighbor regression estimator …
Persistent link: https://www.econbiz.de/10010603674
Saved in:
3
Alternative methods for forecasting GDP.
Guegan, Dominique
;
Rakotomarolahy, Patrick
-
Centre d'Économie de la Sorbonne, Université Paris 1 …
-
2010
nearest neighbor method. We prove also the
asymptotic
normality
of the multivariate k-nearest neighbor regression estimator …
Persistent link: https://www.econbiz.de/10008461116
Saved in:
4
The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting.
Guegan, Dominique
;
Rakotomarolahy, Patrick
-
Centre d'Économie de la Sorbonne, Université Paris 1 …
-
2009
solve this problem. Thanks to new results on the
asymptotic
normality
of the multivariate k-nearest neighbor regression … GDP modelling. Considering dependent mixing data sets, we prove the
asymptotic
normality
of multivariate k …
Persistent link: https://www.econbiz.de/10008622010
Saved in:
5
The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting
Guegan, Dominique
;
Rakotomarolahy, Patrick
-
HAL
-
2009
This article gives the asymptotic properties of multivariate k-nearest neighbor regression estimators for dependent variables belonging to Rd, d 1. The results derived here permit to provide consistent forecasts, and confidence intervals for time series An illustration of the method is given...
Persistent link: https://www.econbiz.de/10010738641
Saved in:
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