Multivariate posterior singular spectrum analysis

被引：0
作者：
Ilkka Launonen
Lasse Holmström
机构：
[1] University of Oulu,Department of Mathematical Sciences
来源：
Statistical Methods & Applications | 2017年 / 26卷
关键词：
Time series; SSA; Bayesian inference; Multivariate; Climate index;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A generalized, multivariate version of the Posterior Singular Spectrum Analysis (PSSA) method is described for the identification of credible features in multivariate time series. We combine Bayesian posterior modeling with multivariate SSA (MSSA) and infer the MSSA signal components with a credibility analysis of the posterior sample. The performance of multivariate PSSA (MPSSA) is compared to the single-variate PSSA with an artificial example and the potential of MPSSA is demonstrated with real data using NAO and SOI climate index series.
引用
收藏
页码：361 / 382
页数：21
相关论文
共 40 条
[11]  
Feliks Y(2012)Baysian scale space analysis of differences in images Technometrics 54 16-29
[12]  
Groth A(2013)Posterior singular spectrum analysis Stat Anal Data Min 6 387-402
[13]  
Robertson A(1997)Extension to the North Atlantic Oscillation using early instrumental pressure observations from Gibraltar and South-West Iceland Int J Climatol 17 1433-1450
[14]  
Ghil M(2010)Computation- and space-efficient implementation of SSA Stat Interface 3 357-368
[15]  
Godtliebsen F(2015)Effects of solar forcing and North Atlantic oscillation on the climate of continental Scandinavia during the Holocene Quatern Sci Rev 112 153-171
[16]  
Marron JS(2013)A scale space multiresolution method for extraction of time series features Stat 2 273-291
[17]  
Chaudhuri P(undefined)undefined undefined undefined undefined-undefined
[18]  
Golyandina N(undefined)undefined undefined undefined undefined-undefined
[19]  
Golyandina N(undefined)undefined undefined undefined undefined-undefined
[20]  
Korobeynikov A(undefined)undefined undefined undefined undefined-undefined
1234