References
- Clausel, M., J. F. Coeurjolly, and J. Lelong. 2016. Stein estimation of the intensity of a spatial homogeneous Poisson point process. Ann. Appl. Probab. 26 (3):1495–1534.
- Decreusefond, L. 1998. Perturbation analysis and Malliavin calculus. Annals of Applied Probability 8 (2):496–523.
- Decreusefond, L., and N. Savy. 2003. Girsanov Theorem for Filtered Poisson Processes. ArXiv:math/0302046
- Decreusefond, L., and N. Savy. 2006. Anticipative calculus with respect to filtered Poisson processes. Annales de l’Institut Henri Poincare (B) Probability and Statistics 42 (3):343–72.
- Decreusefond, L., and A. S. Üstünel. 1999. Stochastic analysis of the fractional Brownian motion. Potential Anal. 10 (2):177–214.
- Es-Sebaiy, K., I. Ouassou, and Y. Ouknine. 2009. Estimation of the drift of fractional Brownian motion. Stat. Probab. Lett. 79:1647–53.
- Jacod, J. 1979. Calcul stochastique et problèmes de martingales. volume 714 of Lecture Notes in Mathematics. Berlin: Springer.
- Kuhn, C. 2002. Shocks and choices-an analysis of incomplete market models, Ph.D. Thesis, Munich University of Technology.
- Liu, J. 2013. Remarks on parameter estimation for the drift of fractional brownian sheet. Acta Mathematica Vietnamica 38 (2):241–53.
- Musta, E., M. Pratelli, and D. Trevisan. 2017. Functional Cramér-Rao bounds and Stein estimators in Sobolev spaces, for Brownian motion and Cox processes. Journal of Multivariate Analysis 154 :135–46.
- Parzen, E. 1999. Stochastic processes, volume 24 of Classics in Applied Mathematics. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA. Reprint of the 1962 original.
- Privault, N., and A. Réveillac. 2008. Stein estimation for the drift of Gaussian processes using the Malliavin calculus. Ann. Stat. 36:2531–50.
- Privault, N., and A. Réveillac. 2009. Stein estimation of Poisson process intensities. Stat Infer Stoch Process 12:37–53, doi:10.1007/s11203-007-9018-8.
- Samorodnitsky, G. 1996. A class of shot noise models for financial applications. In Athens Conference on Applied Probability and time Series Analysis, Vol. I (1995), volume 14 of Lecture Notes in Statist., pages 332–53. New York: Springer.
- Snyder, D. L., and M. I. Miller. 1991. Random Point Processes in Time and Space. New York: Springer-Verlag.
- Yue, S., and M. Hishino. 2001. The general cumulants for a filtered point processes. Applied Mathematical Modeling 25:193–201.