On the Regression of a Random Variable with Respect to a Stochastic Process and, Possibly, p Random Variables
Publications mathématiques et informatique de Rennes (1966-1967)
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topLegoupil, J.. "On the Regression of a Random Variable with Respect to a Stochastic Process and, Possibly, p Random Variables." Publications mathématiques et informatique de Rennes (1966-1967): 1-20. <http://eudml.org/doc/273668>.
@article{Legoupil1966-1967,
author = {Legoupil, J.},
journal = {Publications mathématiques et informatique de Rennes},
language = {eng},
pages = {1-20},
publisher = {Département de Mathématiques et Informatique, Université de Rennes},
title = {On the Regression of a Random Variable with Respect to a Stochastic Process and, Possibly, p Random Variables},
url = {http://eudml.org/doc/273668},
year = {1966-1967},
}
TY - JOUR
AU - Legoupil, J.
TI - On the Regression of a Random Variable with Respect to a Stochastic Process and, Possibly, p Random Variables
JO - Publications mathématiques et informatique de Rennes
PY - 1966-1967
PB - Département de Mathématiques et Informatique, Université de Rennes
SP - 1
EP - 20
LA - eng
UR - http://eudml.org/doc/273668
ER -
References
top- (1) R.A. Fisher : The influence of rainfall on the yield of wheat at Rothamstead (Philo. Trans, of the Royal Stat. So.London Series B, vol. 213, p. 89-142).
- (2) D. Dugue : Traité de statistique théorique et appliquée, Paris (Masson1958). Zbl0084.14305
- (3) Gabriel and Neumann : A Markov chain model for daily rainfall occurence at Tell Aviv (Quart. Journal Royal meteorological So.88, 90 - 95 , 1962)
- (4) Jean Legoupil : 4 notes, Comptes rendus aca. Sci.Paris, T. 249, p. 1444 T. 254, p. 621, T. 255, p. 634, T. 255, p. 2903 from 1959 to 1962 announcing results developed in the following.
- (5) Jean Legoupil : Sur la regression, la corrélation et la dépendance de probabilité d'une variable aléatoire par rapport à une fonction aléatoire (Public. Inst. Stat. Uni.Paris, Fasc. 3 et 4, p. 165 - 314) 1963. Zbl0126.35102
- (6) Jean Legoupil : Advances in the statistical study of a finite set of random variables and a stochastic process by regression methods. Contributed paper presented at the European meeting of Statisticians, London Sept. 1966.
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