Gärtner–Ellis condition for squared asymptotically stationary Gaussian processes
Volume 2, Issue 3 (2015): PRESTO-2015, pp. 267–286
Pub. online: 2 October 2015
Type: Research Article
Open Access
1
This research was supported by Laboratoire d’Excellence TOUCAN (Toulouse Cancer).
Received
19 June 2015
19 June 2015
Revised
18 September 2015
18 September 2015
Accepted
18 September 2015
18 September 2015
Published
2 October 2015
2 October 2015
Abstract
We establish the Gärtner–Ellis condition for the square of an asymptotically stationary Gaussian process. The same limit holds for the conditional distribution given any fixed initial point, which entails weak multiplicative ergodicity. The limit is shown to be the Laplace transform of a convolution of gamma distributions with Poisson compound of exponentials. A proof based on the Wiener–Hopf factorization induces a probabilistic interpretation of the limit in terms of a regression problem.
References
Benitz, G.R., Bucklew, J.A.: Large deviation rate calculations for nonlinear detectors in Gaussian noise. IEEE Trans. Inf. Theory 36(2), 358–371 (1990). MR1052787. doi:10.1109/18.52482
Bingham, N.H.: Szegő’s theorem and its probabilistic descendants. Probab. Surv. 9, 287–324 (2012). MR2956573
Bondesson, L.: Generalized Gamma Convolutions and Related Classes of Distributions. Lect. Notes Stat., vol. 76. Springer (1992). MR1224674. doi:10.1007/978-1-4612-2948-3
Böttcher, A., Silbermann, B.: Introduction to Large Truncated Toeplitz Matrices. Springer (1999). MR1724795. doi:10.1007/978-1-4612-1426-7
Bryc, W., Dembo, A.: Large deviations for quadratic functionals of Gaussian processes. J. Theor. Probab. 10, 307–332 (1997). MR1455147. doi:10.1023/A:1022656331883
Dembo, A., Zeitouni, O.: Large Deviations Techniques and Applications, 2nd edn. Springer (1998). MR1619036. doi:10.1007/978-1-4612-5320-4
Feller, W.: An Introduction to Probability Theory and Its Applications vol. II, 2nd edn. Wiley, London (1971). MR0270403
Grenander, U., Szegő, G.: Toeplitz Forms and Their Applications, 2nd edn. Chelsea, New York (1984). MR0890515
Hannan, E.J.: Multiple Time Series. Wiley, New York (1970). MR0279952
Kallenberg, O.: Foundations of Modern Probability. Springer (1997). MR1464694
Kleptsyna, M.L., Le Breton, A., Viot, M.: New formulas concerning Laplace transforms of quadratic forms for general Gaussian sequences. J. Appl. Math. Stoch. Anal. 15(4), 309–325 (2002). MR1950568. doi:10.1155/S1048953302000266
Kleptsyna, M.L., Le Breton, A., Ycart, B.: Exponential transform of quadratic functional and multiplicative ergodicity of a Gauss–Markov process. Stat. Probab. Lett. 87, 70–75 (2014). MR3168937. doi:10.1016/j.spl.2013.12.023
Kontoyiannis, I., Meyn, S.P.: Spectral theory and limit theorems for geometrically ergodic Markov processes. Ann. Appl. Probab. 13(1), 304–362 (2003). MR1952001. doi:10.1214/aoap/1042765670
Krein, M.G.: Integral equations on the half-line with a kernel depending on the difference of the arguments. Usp. Mat. Nauk 13(5), 3–120 (1958). MR0102721
Louhichi, S., Ycart, B.: Exponential growth of bifurcating processes with ancestral dependence. Adv. Appl. Probab. 47(2), 545–564 (2015). MR3360389. doi:10.1239/aap/1435236987
Marcus, M.B., Rosen, J.: Existence of a critical point for the infinite divisibility of squares of Gaussian vectors in ${R}^{2}$ with non-zero mean. Electron. J. Probab. 14(48), 1417–1455 (2009). MR2519526
Muskhelishvili, N.I.: Singular Integral Equations: Boundary Problems of Function Theory and Their Application to Mathematical Physics, 3rd edn. Dover, New York (2008). MR1215485
Yurinsky, V.: Sums and Gaussian Vectors. Lect. Notes Math., vol. 1617. Springer (1995). MR1442713