Title Prediction from a random time point
Authors Georg Lindgren
Alternative Location http://www.jstor.org/stable..., Restricted Access
Publication The Annals of Probability
Year 1975
Volume 3
Issue 3
Pages 412 - 423
Document type Article
Status Published
Quality controlled Yes
Language eng
Publisher Institute of Mathematical Statistics
Abstract English In prediction (Wiener-, Kalman-) of a random normal process $\{X(t), t \in R\}$ it is normally required that the time $t_0$ from which prediction is made does not depend on the values of the process. If prediction is made only from time points at which the process takes a certain value $u,$ given a priori, ("prediction under panic"), the Wiener-prediction is not necessarily optimal; optimal should then mean best in the long run, for each single realization. The main theorem in this paper shows that when predicting only from upcrossing zeros $t_\nu$, the Wiener-prediction gives optimal prediction of $X(t_\nu + t)$ as $t_\nu$ runs through the set of zero upcrossings, if and only if the derivative $X'(t_\nu)$ at the crossing points is observed. The paper also gives the conditional distribution from which the optimal predictor can be computed.
ISBN/ISSN/Other ISSN: ISSN 0091-1798

Questions: webmaster
Last update: 2013-04-11

Centre for Mathematical Sciences, Box 118, SE-22100, Lund. Telefon: +46 46-222 00 00 (vx)