Eisenbaum, Nathalie; Kaspi, Haya A characterization of the infinitely divisible squared Gaussian processes. (English) Zbl 1102.60031 Ann. Probab. 34, No. 2, 728-742 (2006). The authors deal with the infinite divisibility of the square of a Gaussian process. The main statement is as follows. Let \(\eta \) be a centered Gaussian vector indexed by a finite set \(E\) with a positive definite covariance function \(G(x,y)\), \((x,y)\in E\times E.\) The vector \(\eta ^{2}\) is infinitely divisible if and only if there exists a real-valued function \(d \) on \(E\) such that for any \(x,y\in E\): \[ G(x,y)=d(x)g(x,y)d(y) \]where the function \(g\) is the Green function of a transient symmetric Markov process. Under an additional joint continuity assumption on the covariance function a similar statement holds for a Gaussian process indexed by \( R^{1}.\) At last it is proved that the square of the Brownian sheet is not infinitely divisible. Reviewer: Nijole Kalinauskaitė (Vilnius) Cited in 2 ReviewsCited in 10 Documents MSC: 60G15 Gaussian processes 60E07 Infinitely divisible distributions; stable distributions 60J25 Continuous-time Markov processes on general state spaces 60J55 Local time and additive functionals Keywords:infinite divisibility; Markov processes; local time PDF BibTeX XML Cite \textit{N. Eisenbaum} and \textit{H. Kaspi}, Ann. Probab. 34, No. 2, 728--742 (2006; Zbl 1102.60031) Full Text: DOI arXiv References: [1] Bapat, R. B. (1989). Infinite divisibility of multivariate gamma distribution and \(M\)-matrices. Sankhyā Ser. A 51 73–78. · Zbl 0669.60029 [2] Bass, R., Eisenbaum, N. and Shi, Z. (2000). The most visited sites of symmetric stable processes. Probab. Theory Related Fields 116 391–404. · Zbl 0955.60073 [3] Berman, A. and Plemmons, R. J. (1979). Nonnegative Matrices in the Mathematical Sciences . Academic Press, New York. · Zbl 0484.15016 [4] Cinlar, E. (1975). Introduction to Stochastic Processes . Prentice–Hall, Englewood Cliffs, NJ. · Zbl 0341.60019 [5] Dynkin, E. B. (1983). Local times and quantum fields. In Seminar on Stochastic Processes 82 69–84. Birkhäuser, Boston. · Zbl 0554.60058 [6] Evans, S. N. (1991). Association and infinite divisibility for the Wishart distribution and its diagonal marginals. J. Multivariate Anal. 36 199–203. · Zbl 0719.62063 [7] Eisenbaum, N. (2003). On the infinite divisibility of squared Gaussian processes. Probab. Theory Related Fields 125 381–392. · Zbl 1023.60025 [8] Griffiths, R. C. (1970). Infinite divisible multivariate gamma distributions. Sankhyā Ser. A 32 393–404. · Zbl 0221.60006 [9] Griffiths, R. C. (1984). Characterization of infinitely divisible multivariate gamma distributions. J. Multivariate Anal. 15 12–20. · Zbl 0549.60017 [10] Lévy, P. (1948). The arithmetical character of the Wishart distribution. Proc. Cambridge Philos. Soc. 44 295–297. · Zbl 0030.40602 [11] Marcus, M. B. and Rosen, J. (1992). Sample path properties of the local times of strongly symmetric Markov processes via Gaussian processes. Ann. Probab. 20 1603–1684. · Zbl 0762.60068 [12] Meyer, P. A. (1966). Probabilités et Potentiel . Hermann, Paris. · Zbl 0138.10402 [13] Moran, P. A. P. and Vere-Jones, D. (1969). The infinite divisibility of multi-gamma distributions. Sankhyā Ser. A 31 191–194. · Zbl 0186.51602 [14] Paranjape, S. R. (1978). Simpler proofs for the infinite divisibility of multivariate gamma distributions. Sankhyā Ser. A 40 393–398. · Zbl 0416.60017 [15] Taylor, J. C. (1972). On the existence of sub-Markovian resolvents. Invent. Math. 17 85–93. · Zbl 0229.31014 [16] Taylor, J. C. (1975). A characterization of the kernel \(\lim_\lambda \to 0V_\lambda\) for sub-Markovian resolvents \((V_\lambda)\). Ann. Probab. 3 355–357. · Zbl 0303.60068 [17] Vere-Jones, D. (1967). The infinite divisibility of a bivariate gamma distribution. Sankhyā Ser. A 29 421–422. · Zbl 1204.60023 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.