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| Home > Publications database > jumpdiff : A Python library for statistical inference of jump-diffusion processes in observational or experimental data sets > print |
| Home > Publications database > jumpdiff : A Python library for statistical inference of jump-diffusion processes in observational or experimental data sets > print |
| 001 | 1005789 | ||
| 005 | 20231027114359.0 | ||
| 024 | 7 | _ | |a 10.18637/jss.v105.i04 |2 doi |
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| 037 | _ | _ | |a FZJ-2023-01634 |
| 082 | _ | _ | |a 510 |
| 100 | 1 | _ | |a Gorjão, Leonardo Rydin |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a jumpdiff : A Python library for statistical inference of jump-diffusion processes in observational or experimental data sets |
| 260 | _ | _ | |a Los Angeles, Calif. |c 2023 |b UCLA, Dept. of Statistics |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a We introduce a Python library, called jumpdiff, which includes all necessary functions to assess jump-diffusion processes. This library includes functions which compute a set of non-parametric estimators of all contributions composing a jump-diffusion process, namely the drift, the diffusion, and the stochastic jump strengths. Having a set of measurements from a jump-diffusion process, jumpdiff is able to retrieve the evolution equation producing data series statistically equivalent to the series of measurements. The back-end calculations are based on second-order corrections of the conditional moments expressed from the series of Kramers-Moyal coefficients. Additionally, the library is also able to test if stochastic jump contributions are present in the dynamics underlying a set of measurements. Finally, we introduce a simple iterative method for deriving secondorder corrections of any Kramers-Moyal coefficient. |
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| 700 | 1 | _ | |a Witthaut, Dirk |0 P:(DE-Juel1)162277 |b 1 |u fzj |
| 700 | 1 | _ | |a Lind, Pedro G. |0 P:(DE-HGF)0 |b 2 |
| 773 | _ | _ | |a 10.18637/jss.v105.i04 |g Vol. 105, no. 4 |0 PERI:(DE-600)2010240-9 |n 4 |p 1 |t Journal of statistical software |v 105 |y 2023 |x 1548-7660 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/1005789/files/v105i04-1.pdf |y OpenAccess |
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