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A wavelet-based time-varying autoregressive model for non-stationary and irregular time series
Authors:G E Salcedo  R F Porto  S Y Roa  F R Momo
Institution:1. Department of Mathematics , University of Quindío , Carrera 15 Calle 12N, Armenia , Colombia;2. Department of Operating Assets Restructuring , Bank of Brazil, Brasília , Brazil;3. Institute of Science, National University of General Sarmiento , Buenos Aires , Argentina
Abstract:In this work we propose an autoregressive model with parameters varying in time applied to irregularly spaced non-stationary time series. We expand all the functional parameters in a wavelet basis and estimate the coefficients by least squares after truncation at a suitable resolution level. We also present some simulations in order to evaluate both the estimation method and the model behavior on finite samples. Applications to silicates and nitrites irregularly observed data are provided as well.
Keywords:irregularly spaced time series  locally stationary processes  autoregressive model  multiresolution analysis  wavelets
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