A test statistic for graphical modelling of multivariate time series

Biometrika

Volumn 93, Issue 2, 2006, Pages 399-409

  Matsuda, Yasumasa ^a  

^a TOHOKU UNIVERSITY   (Japan)

Author keywords

Asymptotic normality; Backward stepwise selection; Conditional independence; Graphical model; Kullback Liebler divergence; Periodogram; Spectral density matrix; Test statistic

Indexed keywords

EID: 33745594287     PISSN: 00063444     EISSN: 14643510     Source Type: Journal    
DOI: 10.1093/biomet/93.2.399     Document Type: Article

References (9)

1. BELTRAO, K. I. & BLOOMFIELD, P. (1987). Determining the bandwidth of a kernel spectrum estimate. J. Time Ser. Anal. 8, 21-38.
2. BRILLINGER, D. R. (1981). Time Series: Data Analysis and Theory. New York: Holt, Rinehart and Winston.
3. DAHLHAUS, R. (2000). Graphical interaction models for multivariate time series. Metrika 51, 151-72.
4. LAURITZEN, S. L. (1996). Graphical Models. New York: Oxford University Press.
5. MATSUDA, Y. & YAJIMA, Y. (2004). On testing for separable correlations of multivariate time series. J. Time Ser. Anal. 25, 501-28.
6. MATSUDA, Y., YAJIMA, Y. & TONG, H. (2006). Selecting models with different spectral density matrix structures by the cross-validated log likelihood criterion. Bernoulli 12, 221-49.
7. ŠIDÁK, Z. (1967). Rectangular confidence regions for the means of multivariate normal distributions. J. Am. Statist. Assoc. 62, 626-33.
8. SPEED, T. P. & KIIVERI, H. (1986). Gaussian Markov distributions over finite graphs. Ann. Statist. 14, 138-50.
9. WERMUTH, N. & SCHEIDT, E. (1977). Fitting a covariance selection model to a matrix. Algorithm AS105. Appl. Statist. 26, 88-92.