필터링된 잔차를 이용한 희박벡터자기회귀모형에서의 변수 선택 측도 = Filtered Coupling Measures for Variable Selection in Sparse Vector Autoregressive Modeling

다국어 초록 (Multilingual Abstract)

Vector autoregressive (VAR) models in high dimension suffer from noisy estimates, unstable predictions and hard interpretation. Consequently, the sparse vector autoregressive (sVAR) model, which forces many small coefficients in VAR to exactly zero, has been suggested and proven effective for the modeling of high dimensional time series data. This paper studies coupling measures to select non-zero coefficients in sVAR. The basic idea based on the simulation study reveals that removing the effect of other variables greatly improves the performance of coupling measures. sVAR model coefficients are asymmetric; therefore, asymmetric coupling measures such as Granger causality improve computational costs. We propose two asymmetric coupling measures, filtered-cross-correlation and filtered-Granger-causality, based on the filtered residuals series. Our proposed coupling measures are proven adequate for heavy-tailed and high order sVAR models in the simulation study.

참고문헌 (Reference)

1 Brillinger, D. R., "Time Series: Data Analysis and Theory, 36" SIAM 1981

2 Hsu, N. -J., "Subset selection for vector autoregressive processes using lasso" 52 : 3645-3657, 2008

3 Davis, R. A., "Sparse vector autoregressive modeling"

4 Haufe, s., "Sparse causal discovery in multivariate time series" 6 : 97-106, 2010

5 Bernanke, B. S., "Measuring the effects of monetary policy: A factoraugmented vector autoregressive (FAVAR) approach" National Bureau of Economic Research 2004

6 Sims, C. A., "Macroeconomics and reality" 1-48, 1980

7 Song, S., "Large vector autoregressions"

8 Granger, C. W., "Investigating causal relations by econometric models and cross-spectral methods" 37 : 424-438, 1969

9 Dahlhaus, R., "Identification of synaptic connections in neural ensembles by graphical models" 77 : 93-107, 1997

10 Dahlhaus, R., "Graphical interaction models for multivariate time series" 51 : 157-172, 2000

11 Valdes-Sosa, P. A, "Estimating brain functional connectivity with sparse multivariate autoregression" 360 : 969-981, 2005

12 Reinsel, G. C., "Elements of Multivariate Time Series Analysis" 2003