Abstract
Covariance and independence, rotational symmetry, isonormal Gaussian process, independent increments, Brownian motion and bridge, scaling and inversion, Gaussian Markov processes, quadratic variation, path irregularity, strong Markov and reflection properties, Bessel processes, maximum process, arcsine and uniform laws, laws of the iterated logarithm, Wiener integral, spectral and moving-average representations, Ornstein–Uhlenbeck process, multiple Wiener–Itô integrals, chaos expansion of variables and processes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kallenberg, O. (2021). Gaussian Processes and Brownian Motion. In: Foundations of Modern Probability . Probability Theory and Stochastic Modelling, vol 99. Springer, Cham. https://doi.org/10.1007/978-3-030-61871-1_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-61871-1_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-61870-4
Online ISBN: 978-3-030-61871-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)