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Iterative Algorithm for Time Series Decomposition into Trend and Seasonality: Testing Using the Example of CO(2) Concentrations in the Atmosphere
An iterative algorithm for the decomposition of data series into trend and residual (including the seasonal effect) components is proposed. This algorithm is based on the approaches proposed by the authors in several previous studies and allows unbiased estimates for the trend and seasonal component...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Pleiades Publishing
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8771177/ http://dx.doi.org/10.1134/S0001433821080028 |