Measuring time series predictability using support vector regression (2008)
- Authors:
- Autor USP: MORETTIN, PEDRO ALBERTO - IME
- Unidade: IME
- Assunto: ANÁLISE DE SÉRIES TEMPORAIS
- Language: Inglês
- Imprenta:
- Publisher place: Philadelphia
- Date published: 2008
- Source:
- Título: Communications in Statistics - Simulation and Computation
- ISSN: 0361-0918
- Volume/Número/Paginação/Ano: 2008
-
ABNT
SATO, João Ricardo et al. Measuring time series predictability using support vector regression. Communications in Statistics - Simulation and Computation, 2008Tradução . . Acesso em: 15 mar. 2026. -
APA
Sato, J. R., Costafreda, S., Morettin, P. A., & Brammer, M. J. (2008). Measuring time series predictability using support vector regression. Communications in Statistics - Simulation and Computation. -
NLM
Sato JR, Costafreda S, Morettin PA, Brammer MJ. Measuring time series predictability using support vector regression. Communications in Statistics - Simulation and Computation. 2008 ;[citado 2026 mar. 15 ] -
Vancouver
Sato JR, Costafreda S, Morettin PA, Brammer MJ. Measuring time series predictability using support vector regression. Communications in Statistics - Simulation and Computation. 2008 ;[citado 2026 mar. 15 ] - Indirect estimation of randomized generalized autoregressive conditional heteroskedastic models
- Utilização de ondaletas em modelos com mudança de regime
- Wavelets in state space models
- Estimation of semiparametric models with errors following a scale mixture of Gaussian distributions
- Comparing non-stationary and irregularly spaced time series
- Walsh-function analysis of a certain class of time series
- Limit theorems for stationary and dyadic-stationary processes
- A note on a central limit theorem for dependent random variables
- Análise Bayesiana do modelo Tarso
- Estimation of the Walsh spectrum (Corresp.)
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