Métodos de reamostragem de séries temporais baseados em wavelets. / Resampling methods for time series based on wavelets.
AUTOR(ES)
Ronaldo Mendes Evaristo
DATA DE PUBLICAÇÃO
2010
RESUMO
This paper reviews resampling methods based on wavelets as an alternative to the classic approaches which are, made in the time and frequency domains. These methods, known in the literature as wavestrap and wavestrapping, make use, respectively, of the discrete wavelet transform (DWT) and of the discrete wavelet packet transform (DWPT). Since only few results are avaliable when the DWPT is applied, this text can be considered a contribution to the subject. Here we, also show the superiority of wavestrapping over wavestrap when they are applied to the estimation of power spectral densities of the synthetic time series generated from autoregressive models. These series have an interesting feature that are sharp peaks in their spectral representation, so that most of the traditional methods of resampling lead to biased results.
ASSUNTO(S)
time series analysis análise de ondaletas spectral analysis análise espectral wavelets analysis análise de séries temporais
