Statistical Inference for Stochastic Processes
An International Journal devoted to Time Series Analysis and the Statistics of Continuous Time Processes and Dynamical Systems
Statistical Inference for Stochastic Processes is an international journal publishing articles on parametric and nonparametric inference for discrete- and continuous-time stochastic processes, and their applications to biology, chemistry, physics, finance, economics, and other sciences.
Peer review is conducted using Editorial Manager®, supported by a database of international experts. This database is shared with the journal, Extremes.
Estimation of the lead–lag parameter between two stochastic processes driven by fractional Brownian motions
Kohei Chiba (October 2019)
- Journal Title
- Statistical Inference for Stochastic Processes
- Volume 1 / 1998 - Volume 22 / 2019
- Print ISSN
- Online ISSN
- Springer Netherlands
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