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.
Kou Fujimori (October 2018)
Estimation of the bias parameter of the skew random walk and application to the skew Brownian motion
Antoine Lejay (October 2018)
- Journal Title
- Statistical Inference for Stochastic Processes
- Volume 1 / 1998 - Volume 21 / 2018
- Print ISSN
- Online ISSN
- Springer Netherlands
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