Nonparametric estimation for fractional diffusion processes with random effects
We propose a nonparametric estimation for a class of fractional stochastic differential equations (FSDE) with random effects. We precisely consider general linear fractional stochastic differential equations with drift depending on random effects and non-random diffusion. We build ordinary kernel es...
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| creator | Omari, M. El Maroufy, H. El Fuchs, C |
| description | We propose a nonparametric estimation for a class of fractional stochastic
differential equations (FSDE) with random effects. We precisely consider
general linear fractional stochastic differential equations with drift
depending on random effects and non-random diffusion. We build ordinary kernel
estimators and histogram estimators and study their Lp-risk (p =1 or 2), when
H>1/2. Asymptotic results are evaluated as both T = T(N) and N tend to
infinity. |
| doi_str_mv | 10.48550/arxiv.1901.05547 |
| format | Article |
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differential equations (FSDE) with random effects. We precisely consider
general linear fractional stochastic differential equations with drift
depending on random effects and non-random diffusion. We build ordinary kernel
estimators and histogram estimators and study their Lp-risk (p =1 or 2), when
H>1/2. Asymptotic results are evaluated as both T = T(N) and N tend to
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differential equations (FSDE) with random effects. We precisely consider
general linear fractional stochastic differential equations with drift
depending on random effects and non-random diffusion. We build ordinary kernel
estimators and histogram estimators and study their Lp-risk (p =1 or 2), when
H>1/2. Asymptotic results are evaluated as both T = T(N) and N tend to
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differential equations (FSDE) with random effects. We precisely consider
general linear fractional stochastic differential equations with drift
depending on random effects and non-random diffusion. We build ordinary kernel
estimators and histogram estimators and study their Lp-risk (p =1 or 2), when
H>1/2. Asymptotic results are evaluated as both T = T(N) and N tend to
infinity.</abstract><doi>10.48550/arxiv.1901.05547</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Mathematics - Statistics Theory Statistics - Theory |
| title | Nonparametric estimation for fractional diffusion processes with random effects |
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