SIML Filtering Method for Noisy Non-stationary Economic Time Series

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In this book, we explain the development of a new filtering method to estimate the hidden states of random variables for multiple non-stationary time series data. This method is particularly helpful in analyzing small-sample non-stationary macro-economic time series. The method is based on the frequency-domain application of the separating information maximum likelihood (SIML) method, which was pr...

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In this book, we explain the development of a new filtering method to estimate the hidden states of random variables for multiple non-stationary time series data. This method is particularly helpful in analyzing small-sample non-stationary macro-economic time series. The method is based on the frequency-domain application of the separating information maximum likelihood (SIML) method, which was pr...

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  • Formats: epub
  • ISBN: 9789819608829
  • Publication Date: 3 Mar 2025
  • Publisher: Springer Nature Singapore
  • Product language: English
  • Drm Setting: DRM