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| COMBINING SINGULAR SPECTRUM ANALYSIS AND PAR（p） STRUCTURES TO MODEL WIND SPEED TIME SERIES | |
| 作者姓名： | MENEZES Moises Lima de SOUZA Reinaldo Castro PESSANHA Jos Francisco Moreira |
| 作者单位： | [1]Department of Statistics, Fluminense Federal University （ UFI~, Brazil. Email： moisesAima@msn.com.SOUZA Reinaldo Castro [2]Electrical Engineering Department： Pontifical Catholic University of Rio de Janeiro （PUC-Rio）, Brazil. [3]Institute of Mathematics and Statistics, State University of Rio de Janeiro （UERJ）, Brazil. |
| 摘 要： | Singular spectrum analysis （SSA） is a technique that decomposes a time series into a set of components, such as, trend, harmonics, and residuals. Leaving out the residual components and adding up the others, the time series can be smoothed. This procedure has been used to model Brazilian electricity consumption and flow series. The PAR（p）, periodic autoregressive models, has been broadly used in modelling energy series in Brazil. This paper presents an approach of this decomposition method, by fitting the PAR（p）, considering its multivariate version known as multivariate SSA （MSSA）. The method was applied to a vector of two wind speed series recorded at two locations in the Brazilian Northeast region. The obtained results, when compared to the univariate decomposition of each series, were far superior, showing that the spatial correlation between the two series were considered by MSSA decomposition stage. |
| 关 键 词： | 奇异谱分析 PAR 风速 结构 时间序列 分解方法 自回归模型 东北部地区 |
Combining singular spectrum analysis and PAR(p) structures to model wind speed time series |
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| MENEZES Moises Lima de,SOUZA Reinaldo Castro,PESSANHA Jos Francisco Moreira.Combining singular spectrum analysis and PAR(p) structures to model wind speed time series[J].Journal of Systems Science and Complexity,2014,27(1):29-46. | |
| Authors: | Moisés Lima de Menezes Reinaldo Castro Souza José Francisco Moreira Pessanha |
| Institution: | 1. Department of Statistics, Fluminense Federal University (UFF), Niterói, Brazil 2. Electrical Engineering Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil 3. Institute of Mathematics and Statistics, State University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil |
| Abstract: | Singular spectrum analysis (SSA) is a technique that decomposes a time series into a set of components, such as, trend, harmonics, and residuals. Leaving out the residual components and adding up the others, the time series can be smoothed. This procedure has been used to model Brazilian electricity consumption and flow series. The PAR(p), periodic autoregressive models, has been broadly used in modelling energy series in Brazil. This paper presents an approach of this decomposition method, by fitting the PAR(p), considering its multivariate version known as multivariate SSA (MSSA). The method was applied to a vector of two wind speed series recorded at two locations in the Brazilian Northeast region. The obtained results, when compared to the univariate decomposition of each series, were far superior, showing that the spatial correlation between the two series were considered by MSSA decomposition stage. |
| Keywords: | MSSA periodic autoregressive model SSA wind speed series |
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