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Spectral characterization of the Wold–Zasuhin decomposition and prediction-error operator

Published online by Cambridge University Press:  24 October 2008

S. C. Power
Affiliation:
Department of Mathematics, University of Lancaster, Lancaster LA 1 4YF

Extract

Over thirty years ago Wiener and Masani pointed out in the introduction of their celebrated paper [31] that for a general multivariate stationary stochastic process no relation had been given for the prediction-error matrix in terms of the spectrum of the process. In particular it was unknown how to characterize the rank of the process in spectral terms (cf. Masani[12], p. 369, question 1). Despite explicit progress in this connection with certain regular processes, such as the series representations in [11, 19, 22, 32], or the iterative approach of [28, 29], and despite progress in the structure theory of degenerate processes ([8, 10, 14, 15, 26]), a general relation or series expression has remained elusive.

Type
Research Article
Copyright
Copyright © Cambridge Philosophical Society 1991

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References

REFERENCES

[1]Arveson, W. B.. Interpolation problems in nest algebras. J. Funct. Anal. 20 (1975), 208233.CrossRefGoogle Scholar
[2]Cuoi, M. D.. Some assorted inequalities for positive linear maps on C*-algebras. J. Operator Theory 4 (1980), 271285.Google Scholar
[3]Devinatz, A.. The factorization of operator valued functions. Ann. of Math. 73 (1961), 458459.CrossRefGoogle Scholar
[4]Doob, J. L.. Stochastic Processes (Wiley, 1953).Google Scholar
[5]Douglas, R. C.. On factoring positive operator functions. J. Math. Mech. 16 (1966), 119126.Google Scholar
[6]Douglas, R. C.. Local Toeplitz operators. Proc. London Math. Soc. (3) 36 (1978), 243472.CrossRefGoogle Scholar
[7]Helson, H.. Lectures on Invariant Subspaces (Academic Press, 1964).Google Scholar
[8]Helson, H. and Lowdernlager, D.. Prediction theory and Fourier series in several variables. Acta Math. 99 (1958), 165201.CrossRefGoogle Scholar
[9]Lance, E. C.. Cohomology and perturbation of nest algebras. Proc. London Math. Soc. (3) 43 (1981), 334356.Google Scholar
[10]Masani, P.. Cramer's theorem on monotone matrix-valued functions and the Wold decomposition. In Probability and Statistics (ed. Grenander, U.), pp. 175189.Google Scholar
[11]Masani, P.. The prediction theory of multivariate stochastic processes III. Acta Math. 104 (1960), 141162.CrossRefGoogle Scholar
[12]Masani, P.. Recent trends in multivariate prediction theory. In Multivariate Analysis (ed. Krishnaiah, P. R.) (Academic Press, 1966), pp. 351382.Google Scholar
[13]Masani, P.. The place of multiplicative integration in modern analysis. Appendix II of Product Integration with Applications to Differential Equations, Encyclopedia of Mathematics and its Applications, vol. 10 (Addison Wesley, 1979).Google Scholar
[14]Matveev, R. F.. On multidimensional regular stationary processes. Theory Probab. Appl. 5 (1960), 3339.Google Scholar
[15]Niemi, H.. Subordination, rank, and determinism of multivariate stationary sequences. J. Multivariate Anal.a 15 (1984), 99123.CrossRefGoogle Scholar
[16]Page, L. B.. Bounded, compact and vectorial Hankel operators. Trans. Amer. Math. Soc. 150 (1970), 529539.Google Scholar
[17]Peller, V. V.. Vectorial Hankel operators, commutators and related operators of the Schatten–von Neumann class Cp. J. Integral Equation. 5 (1982), 244272.Google Scholar
[18]Peller, V. V. and Hruscev, S. V.. Hankel operators, best approximation and stationary Gaussian processes. Uspekhi Mat. Nauk. 37 (1982), 53124.Google Scholar
[19]Poueahmadi, M.. A matricial extension of the Helson–Szego theorem and its application in multivariate prediction. J. Multivariate Anal. 16 (1965), 265275.CrossRefGoogle Scholar
[20]Power, S. C.. Nuclear operators in nest algebras. J. Operator Theory 10 (1983), 337352.Google Scholar
[21]Power, S. C.. Factorization in analytic operator algebras. J. Funct. Anal. 67 (1986), 413432.CrossRefGoogle Scholar
[22]Rosanov, Y. A.. Stationary Random Processes (Holden Day, 1967).Google Scholar
[23]Rosenblum, M. and Rovnyak, J.. The factorization problem for non-negative operator-valued functions. Bull. Amer. Math. Soc. 77 (1971), 287318.CrossRefGoogle Scholar
[24]Sarason, D.. Functions of vanishing mean oscillations. Trans. Amer. Math. Soc. 207 (1973), 286299.Google Scholar
[25]Smul'jan, Ju. L.. An operator Hellinger integral. Mat. Sb. 91 (1959), 381430.Google Scholar
[26]Suciu, I. and Valusescu, I.. Factorization theorems and prediction theory. Rev. Roumaine Math. Pures Appl. 23 (1978), 13931423.Google Scholar
[27]Sz-Nagy, B. and Fotaş, C.. Harmonic Analysis of Hilbert Space Operators (North Holland, 1970).Google Scholar
[28]Wilson, G. Tunnicliffe. The factorization of matricial spectral densities. SIAM. J. Appl. Math. 23 (1972), 420426.CrossRefGoogle Scholar
[29]Wilson, G. Tunnicliffe. A convergence theorem for spectral factorization. J. Multivariate Anal. 8 (1978), 222232.CrossRefGoogle Scholar
[30]Wiener, N. and Akutowicz, E. J.. A factorization of positive hermitian matrices. J Math. Mech. 8 (1959), 111120.Google Scholar
[31]Wiener, N. and Masani, P.. The prediction theory of multivariate stochastic processes. Part I, Acta Math. 98 (1957), 111150.CrossRefGoogle Scholar
[32]Wiener, N. and Masani, P.. The prediction theory of multivariate stochastic processes. Part II, Acta Math. 99 (1958), 93137.CrossRefGoogle Scholar