Title :

ESTIMATION OF THE SMOOTHING PARAMETERS IN THE HPMV FILTER

Author(s) :

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

Journal title :

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

Publisher :

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

Publication date :

2011

English keyword(s) :

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

HAL domain(s) :

Mathématiques [math]

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL