Random Functions
Mircea Grigoriu ()
Additional contact information
Mircea Grigoriu: Cornell University
Chapter Chapter 3 in Stochastic Systems, 2012, pp 59-127 from Springer
Abstract:
Abstract General considerations on random functions are followed by essential definitions and properties for these functions. The concepts of weak stationarity and stationarity are defined and illustrated. Mean square continuity, differentiation, and integration as well as spectral and related representations for weakly stationary random functions are discussed extensively. Limitations of second moment calculus are highlighted by the study of sample properties for random functions with finite variance. A broad range of random functions, for example, Gaussian, translation, Markov, martingales, Brownian motion, compound Poisson, and Lévy processes, are examined. Algorithms for generating samples of stationary Gaussian functions, translation models, and non-stationary Gaussian processes conclude our discussion.
Keywords: Brownian Motion; Spectral Density; Covariance Function; Random Function; Translation Model (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-1-4471-2327-9_3
Ordering information: This item can be ordered from
http://www.springer.com/9781447123279
DOI: 10.1007/978-1-4471-2327-9_3
Access Statistics for this chapter
More chapters in Springer Series in Reliability Engineering from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().