An application of chain-dependent processes to meteorology
- 1 June 1977
- journal article
- research article
- Published by Cambridge University Press (CUP) in Journal of Applied Probability
- Vol. 14 (03) , 598-603
- https://doi.org/10.1017/s0021900200025845
Abstract
An explicit formula is derived for the variance normalizing constant in the central limit theorem for chain-dependent processes. As an application to meteorology, a specific chain-dependent process is proposed as a probabilistic model for the sequence of daily amounts of precipitation. This model is a generalization of the commonly used Markov chain model for the occurrence of precipitation.Keywords
This publication has 7 references indexed in Scilit:
- Limit Theorems for Extreme Values of Chain-Dependent ProcessesThe Annals of Probability, 1975
- Limit theorems for sums of chain-dependent processesJournal of Applied Probability, 1974
- Limit laws for maxima of a sequence of random variables defined on a Markov chainAdvances in Applied Probability, 1970
- Extreme Values in Uniformly Mixing Stationary Stochastic ProcessesThe Annals of Mathematical Statistics, 1965
- A central limit theorem for processes defined on a finite Markov chainMathematical Proceedings of the Cambridge Philosophical Society, 1964
- Some Limit Theorems for Stationary ProcessesTheory of Probability and Its Applications, 1962
- A Markov chain model for daily rainfall occurrence at Tel AvivQuarterly Journal of the Royal Meteorological Society, 1962