Barbara Pacchiarotti - Research

Research interest:

Large and moderate deviation principles.

Gaussian measures, conditional Gaussian measures and conditionally Gaussian measures.

Volterra processes. Gaussian Volterra type stochastic volatility models; fractional and rough models.

Preprints:

37. Macci C., Pacchiarotti B. & Torrisi G.L.(2023). Large and moderate deviations for Gaussian neural networks , available at arXiv:2401.01611

36. Baldi P. & Pacchiarotti B.(2022). Large Deviations of continuous Gaussian processes: from small noise to small time, available at arXiv:2207.12037

Publications:

35. Macci C. & Pacchiarotti B.(2024). Asymptotic results for compound sums in Banach Spaces, ESAIM: PROBABILITY AND STATISTICS, 28, 329-349
34. Giuliano R., Macci C. & Pacchiarotti B.(2024). Asymptotic results for sums and extremes. JOURNAL OF APPLIED PROBABILITY, 61(4), pp. 1153-1171

33. Macci C. & Pacchiarotti B.(2024). Large deviations for perturbed Gaussian processes and logarithmic asymptotic estimates for some exit probabilities. THEORY OF PROBABILITY AND MATHEMATICAL STATISTICS, 111 (2024), 21-43

32. Giorgio G., Pacchiarotti B. & Pigato P.(2023). Short-time asymptotics for non self-similar stochastic volatility models. APPLIED MATHEMATICAL FINANCE, 30(3), 123-152.

31. Catalini G. & Pacchiarotti B.(2023). Asymptotics for multifactor Volterra type stochastic volatility models. STOCHASTIC ANALYSIS AND APPLICATIONS, 41(6), 1025-1055.

30. Macci C. & Pacchiarotti B.(2023). Asymptotic results for certain first-passage times and areas of renewal processes. THEORY OF PROBABILITY AND MATHEMATICAL STATISTICS, 108, 127-148.

29. Macci C., Pacchiarotti B. & Villa E. (2022). Asymptotic results for families of power series distributions. MODERN STOCHASTICS: THEORY AND APPLICATIONS, 9(2), 207-228.

28. Calì C, Longobardi M., Macci C. & Pacchiarotti B.(2022). Asymptotic results for linear combinations of spacings generated by i.i.d. exponential random variables. METRIKA, 85, 733-752.

27. Leonenko N., Macci C. & Pacchiarotti, B. (2021). Large deviations for a class of tempered subordinators and their inverse processes. Proceedings of the Royal Society of Edinburgh. Section A. Mathematics, 151(6), 2030-2050.

26. Cellupica M. & Pacchiarotti B. (2021). Pathwise asymptotics for Volterra type stochastic volatility models. JOURNAL OF THEORETICAL PROBABILITY, 34(2), 682–727.

25. Pacchiarotti B. (2020). Some large deviations principles for time changed Gaussian processes. LITHUANIAN MATHEMATICAL JOURNAL, 60(4), 513-529.

24. Pacchiarotti B. (2020). Optimal importance sampling for continuous Gaussian fields. JOURNAL OF APPLIED ANALYSIS, 26(2), 161–171.

23. Pacchiarotti B. (2020). Pathwise asymptotics for Volterra processes conditioned to a noisy version of the Brownian motion. MODERN STOCHASTICS: THEORY AND APPLICATIONS, 7(1), 17-41

22. Giuliano R., Macci, C. & Pacchiarotti B. (2020). Asymptotic results for weighted means of linear combinations of independent Poisson random variables. STOCHASTICS, 92(4), 497-518.

21. Pacchiarotti B. (2019). Large deviations for generalized conditioned Gaussian processes and their bridges. PROBABILITY AND MATHEMATICAL STATISTICS, 39(2),158-181.

20. Giuliano R., Macci C. & Pacchiarotti B. (2019). Large deviations for weighted means of random vectors defined in terms of suitable Lévy processes. STATISTICS & PROBABILITY LETTERS, 150, 13-22.

19. Pacchiarotti B. & Pigliacelli A. (2018). Large deviations for conditionally Gaussian processes: estimates of level crossing probability. MODERN STOCHASTICS: THEORY AND APPLICATIONS, 5(4), 483-499.

18. Macci C. & Pacchiarotti B. (2017). Asymptotic behavior of some hitting probabilities for sums of IID gaussian random sets. COMMUNICATIONS IN STATISTICS. SIMULATION AND COMPUTATION, 46(6), 4318-4332.

17. Macci C. & Pacchiarotti B. (2017). Asymptotic results for finite superpositions of Ornstein–Uhlenbeck processes. STOCHASTIC ANALYSIS AND APPLICATIONS, 35(6), 954-979.

16. Giorgi F. & Pacchiarotti B. (2017). Large deviations for conditional Volterra processes. STOCHASTIC ANALYSIS AND APPLICATIONS, 35(2), 191-210.

15. Macci, C. & Pacchiarotti B. (2017). Exponential tightness for Gaussian processes, with applications to some sequences of weighted means. STOCHASTICS, 89(2), 469-484.

14. Macci, C. & Pacchiarotti B. (2017). Large deviations for estimators of the parameters of a neuronal response latency model. STATISTICS & PROBABILITY LETTERS, 126, 65-75.

13. Macci C. & Pacchiarotti, B. (2017). Large deviations for i.i.d. replications of the total progeny of a Galton–Watson process. MODERN STOCHASTICS: THEORY AND APPLICATIONS, 4(1), 1-13.

12. Macci C. & Pacchiarotti, B. (2015). Asymptotic results for empirical means of independent geometric distributed random variables. STOCHASTICS, 87(2), 308-325.

11. Caramellino L., Pacchiarotti B. & Salvadei S. (2015). Large Deviation Approaches for the Numerical Computation of the Hitting Probability for Gaussian Processes. METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 17(2), 383-401.

10. Macci C. & Pacchiarotti B. (2015). Large deviations for a class of counting processes and some statistical applications. STATISTICS & PROBABILITY LETTERS, 104, 36-48.

9. Giuliano R., Macci, C. & Pacchiarotti, B. (2015). Asymptotic results for runs and empirical cumulative entropies. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 157-158, 77-89.

8. Giuliano R., Macci, C. & Pacchiarotti, B. (2014). On large deviations for some sequences of weighted means of Gaussian processes. JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 414(2), 612-631.

7. Hashorva E., Macci C. & Pacchiarotti, B. (2013). Large Deviations for Proportions of Observations Which Fall in Random Sets Determined by Order Statistics. METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 15(4), 875-896.

6. Caramellino L. & Pacchiarotti B. (2008). Large deviation estimates of the crossing probability for pinned Gaussian processes. ADVANCES IN APPLIED PROBABILITY, 40(2), 424-453.

5. Baldi P., & Pacchiarotti B. (2006). Explicit computation of second-order moments of importance sampling estimators for fractional Brownian motion. BERNOULLI, 12(4), 663-688.

4. Pacchiarotti B., Fanfoni, M. & Tomellini, M. (2005). Roughness in the Kolmogorov-Johnson-Mehl-Avrami framework: extension to (2+1)D of the Trofimov-Park model. PHYSICA. A, 358, 379-392.

3. Caramellino L. & Pacchiarotti B. (2002). Sharp estimates for the hitting probability on time-dependent barriers for a Brownian Motion. MONTE CARLO METHODS AND APPLICATIONS, 8(3), 221-236.

2. Caramellino L., Climescu-Haulica A. & Pacchiarotti, B. (1999). Diffusion approximations for random walks on nilpotent Lie groups. STATISTICS & PROBABILITY LETTERS, 41(4), 363-367.

1. Costantini C., Pacchiarotti B. & Sartoretto, F. (1998). Numerical Approximation for Functionals of Reflecting Diffusion Processes. SIAM JOURNAL ON APPLIED MATHEMATICS, 58(1), 73-102.