Littérature
383
GT13.
C. Graham et D. Talay – Stochastic simulation and Monte Carlo methods, Stochastic Modelling and Applied Probability, vol. 68, Springer,
Heidelberg, 2013, Mathematical foundations of stochastic simulation.
372, 374
Gut13.
A. Gut – Probability : a graduate course, second éd., Springer Texts
in Statistics, Springer, New York, 2013. 373
Häg02.
O. Häggström – Finite markov chains and algorithmic applications,
London Mathematical Society student texts, Cambridge University
Press, 2002. 81, 373
Har60.
T. E. Harris – « A lower bound for the critical probability in a certain
percolation process », Proc. Cambridge Philos. Soc. 56 (1960), p. 13–
20. 227
Har02.
— , The theory of branching processes, Dover Phoenix Editions, Dover
Publications Inc., Mineola, NY, 2002, Corrected reprint of the 1963
original [Springer, Berlin ; MR0163361 (29 #664)]. 54, 241
Has70.
W. K. Hastings – « Monte Carlo sampling methods using Markov
chains and their applications », Biometrika (1970), no. 57, p. 97–109.
81
HH80.
P. Hall et C. C. Heyde – Martingale limit theory and its application,
Academic Press, Inc. [Harcourt Brace Jovanovich, Publishers], New
York-London, 1980, Probability and Mathematical Statistics. 91, 373
HJ06.
O. Häggström et J. Jonasson – « Uniqueness and non-uniqueness
in percolation theory », Probab. Surv. 3 (2006), p. 289–344. 227
HJ13.
R. A. Horn et C. R. Johnson – Matrix analysis, second éd., Cambridge University Press, Cambridge, 2013. 294
HJV07.
P. Haccou, P. Jagers et V. A. Vatutin – Branching processes :
variation, growth, and extinction of populations, Cambridge Studies in
Adaptive Dynamics, Cambridge University Press, Cambridge, 2007. 54
Hol01.
L. Holst – « Extreme value distributions for random coupon collector
and birthday problems », Extremes 4 (2001), no. 2, p. 129–145 (2002).
16
Hop84.
F. M. Hoppe – « Pólya-like urns and the Ewens’ sampling formula »,
J. Math. Biol. 20 (1984), no. 1, p. 91–94. 197
Hör67.
L. Hörmander – « Hypoelliptic second order differential equations »,
Acta Math. 119 (1967), p. 147–171. 354
HV10.
S. Herrmann et P. Vallois – « From persistent random walk to the
telegraph noise », Stoch. Dyn. 10 (2010), no. 2, p. 161–196. 311
IS88.
J. Z. Imbrie et T. Spencer – « Diffusion of directed polymers in a
random environment », J. Statist. Phys. 52 (1988), no. 3-4, p. 609–626.
263
JK77.
N. L. Johnson et S. Kotz – Urn models and their application, John
Wiley & Sons, New York-London-Sydney, 1977, An approach to modern discrete probability theory, Wiley Series in Probability and Mathematical Statistics. 212
383
GT13.
C. Graham et D. Talay – Stochastic simulation and Monte Carlo methods, Stochastic Modelling and Applied Probability, vol. 68, Springer,
Heidelberg, 2013, Mathematical foundations of stochastic simulation.
372, 374
Gut13.
A. Gut – Probability : a graduate course, second éd., Springer Texts
in Statistics, Springer, New York, 2013. 373
Häg02.
O. Häggström – Finite markov chains and algorithmic applications,
London Mathematical Society student texts, Cambridge University
Press, 2002. 81, 373
Har60.
T. E. Harris – « A lower bound for the critical probability in a certain
percolation process », Proc. Cambridge Philos. Soc. 56 (1960), p. 13–
20. 227
Har02.
— , The theory of branching processes, Dover Phoenix Editions, Dover
Publications Inc., Mineola, NY, 2002, Corrected reprint of the 1963
original [Springer, Berlin ; MR0163361 (29 #664)]. 54, 241
Has70.
W. K. Hastings – « Monte Carlo sampling methods using Markov
chains and their applications », Biometrika (1970), no. 57, p. 97–109.
81
HH80.
P. Hall et C. C. Heyde – Martingale limit theory and its application,
Academic Press, Inc. [Harcourt Brace Jovanovich, Publishers], New
York-London, 1980, Probability and Mathematical Statistics. 91, 373
HJ06.
O. Häggström et J. Jonasson – « Uniqueness and non-uniqueness
in percolation theory », Probab. Surv. 3 (2006), p. 289–344. 227
HJ13.
R. A. Horn et C. R. Johnson – Matrix analysis, second éd., Cambridge University Press, Cambridge, 2013. 294
HJV07.
P. Haccou, P. Jagers et V. A. Vatutin – Branching processes :
variation, growth, and extinction of populations, Cambridge Studies in
Adaptive Dynamics, Cambridge University Press, Cambridge, 2007. 54
Hol01.
L. Holst – « Extreme value distributions for random coupon collector
and birthday problems », Extremes 4 (2001), no. 2, p. 129–145 (2002).
16
Hop84.
F. M. Hoppe – « Pólya-like urns and the Ewens’ sampling formula »,
J. Math. Biol. 20 (1984), no. 1, p. 91–94. 197
Hör67.
L. Hörmander – « Hypoelliptic second order differential equations »,
Acta Math. 119 (1967), p. 147–171. 354
HV10.
S. Herrmann et P. Vallois – « From persistent random walk to the
telegraph noise », Stoch. Dyn. 10 (2010), no. 2, p. 161–196. 311
IS88.
J. Z. Imbrie et T. Spencer – « Diffusion of directed polymers in a
random environment », J. Statist. Phys. 52 (1988), no. 3-4, p. 609–626.
263
JK77.
N. L. Johnson et S. Kotz – Urn models and their application, John
Wiley & Sons, New York-London-Sydney, 1977, An approach to modern discrete probability theory, Wiley Series in Probability and Mathematical Statistics. 212