Titre :

ESTIMATION OF THE SMOOTHING PARAMETERS IN THE HPMV FILTER

Auteur(s) :

Rahmania, Nadji []
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Dermoune, Azzouz []
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Djehiche, Boualem []
Department of Mathematics [Sweden] [KTH]

Titre de la revue :

ANALELE S¸TIINT¸ IFICE ALE UNIVERSITAT¸ II “AL.I. CUZA” DIN IAS¸I (S.N.) ˘ MATEMATICA,

Éditeur :

An. Stiint. Univ. Al. I. Cuza Iasi. Mat.

Date de publication :

2011

Mot(s)-clé(s) en anglais :

Mathematics Subject Classification 2000: 62M10 62G15 adaptive estimation Gaussian process Hodrick-Prescott filter noiseto-signal ratio orthogonal parametrization output gap potential output detrending unobserved components models
Mathematics Subject Classification 2000: 62M10
62G15 adaptive estimation
Gaussian process
Hodrick-Prescott filter
noiseto-signal ratio
orthogonal parametrization
output gap
potential output
detrending
unobserved components models

Discipline(s) HAL :

Mathématiques [math]

Résumé en anglais : [en]

We suggest an optimality criterion, for choosing the best smoothing parameters for an extension of the so-called Hodrick-Prescott Multivariate (HPMV) filter. We show that this criterion admits a whole set of optimal smoothing ...
Lire la suite >We suggest an optimality criterion, for choosing the best smoothing parameters for an extension of the so-called Hodrick-Prescott Multivariate (HPMV) filter. We show that this criterion admits a whole set of optimal smoothing parameters, to which belong the widely used noise-to-signal ratios. We also propose explicit consistent estimators of these noise-to-signal ratios, which in turn yield a new performant method to estimate the output gap.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL