Every continuous first order autoregressive stochastic process is a Gaussian process

Friedrich Liese

Kybernetika (1992)

  • Volume: 28, Issue: 3, page 227-233
  • ISSN: 0023-5954

How to cite

top

Liese, Friedrich. "Every continuous first order autoregressive stochastic process is a Gaussian process." Kybernetika 28.3 (1992): 227-233. <http://eudml.org/doc/27744>.

@article{Liese1992,
author = {Liese, Friedrich},
journal = {Kybernetika},
keywords = {independent increments; Gauss-Markov process},
language = {eng},
number = {3},
pages = {227-233},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Every continuous first order autoregressive stochastic process is a Gaussian process},
url = {http://eudml.org/doc/27744},
volume = {28},
year = {1992},
}

TY - JOUR
AU - Liese, Friedrich
TI - Every continuous first order autoregressive stochastic process is a Gaussian process
JO - Kybernetika
PY - 1992
PB - Institute of Information Theory and Automation AS CR
VL - 28
IS - 3
SP - 227
EP - 233
LA - eng
KW - independent increments; Gauss-Markov process
UR - http://eudml.org/doc/27744
ER -

References

top
  1. W. Feller, An Introduction to Probability Theory and 1ts Application, Vol. II. J. Wiley k Sons, New York 1971. (1971) MR0270403
  2. J. Michálek, 1-divergence of some diffusion processes, Problems Control Inform. Theory 19 (1990), 313-338. (1990) MR1074556
  3. A. V. Skorokhod, Processes with Independent Increments (in Russian), Nauka, Moscow 1964. (1964) 
  4. I. Vajda, Distances and discrimination rates for stochastic processes, Stochastic Process. Appl. 35 (1990), 47-57. (1990) Zbl0701.62084MR1062582

NotesEmbed ?

top

You must be logged in to post comments.