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Regular conditional distributions of continuous max-infinitely divisible random fields

  
@article{EJP1991,
	author = {Clément Dombry and Frédéric Eyi-Minko},
	title = {Regular conditional distributions of continuous max-infinitely divisible random fields},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {18},
	year = {2013},
	keywords = {max-infinitely divisible process; max-stable process; regular conditional distribution; point process representation},
	abstract = {This paper is devoted to the  prediction problem in extreme value theory. Our main result is an explicit expression of the  regular conditional distribution of a max-stable (or max-infinitely divisible) process $\{\eta(t)\}_{t\in T}$ given observations $\{\eta(t_i)=y_i,\ 1\leq i\leq k\}$. Our starting point is the point process representation of max-infinitely divisible processes by Giné, Hahn and Vatan (1990). We carefully analyze the structure of the underlying point process, introduce the notions of extremal function, sub-extremal function and hitting scenario associated to the constraints and derive the associated distributions. This allows us to explicit the conditional distribution as a mixture over all hitting scenarios compatible with the conditioning constraints. This formula extends a recent result by Wang and Stoev (2011) dealing with the case of spectrally discrete max-stable random fields. This paper offers new tools and perspective or prediction in extreme value theory together with numerous potential applications.},
	pages = {no. 7, 1-21},
	issn = {1083-6489},
	doi = {10.1214/EJP.v18-1991},    
        url = {http://ejp.ejpecp.org/article/view/1991}}