ESAIM: Probability and Statistics (ESAIM: P&S)

ESAIM: P&S publishes original research and survey papers in the area of Probability and Statistics. It covers theoretical and practical aspects, in any field of these domains. Read more

Central limit theorem for supercritical binary homogeneous Crump-Mode-Jagers processes

Benoît Henry

ESAIM: PS, 21 (2017) 113-137

Published online: 19 October 2017

DOI: https://doi.org/10.1051/ps/2016029
- PDF (422.9 KB)
- References
Minimax regression estimation for Poisson coprocess

Benoît Cadre, Nicolas Klutchnikoff and Gaspar Massiot

ESAIM: PS, 21 (2017) 138-158

Published online: 19 October 2017

DOI: https://doi.org/10.1051/ps/2017004
- PDF (290.8 KB)
- References
Quasi-ergodicity for absorbing Markov processes via deviation inequality

Jinwen Chen and Siqi Jian

ESAIM: PS, 21 (2017) 159-167

Published online: 19 October 2017

DOI: https://doi.org/10.1051/ps/2017009
- PDF (173.1 KB)
- References
L^p-Solutions of backward doubly stochastic differential equations with stochastic Lipschitz condition and p ∈ (1,2)

Jean-Marc Owo

ESAIM: PS, 21 (2017) 168-182

Published online: 19 October 2017

DOI: https://doi.org/10.1051/ps/2017008
- PDF (242.3 KB)
- References
A note on upper-patched generators for Archimedean copulas

Elena Di Bernardino and Didier Rullière

ESAIM: PS, 21 (2017) 183-200

Published online: 19 October 2017

DOI: https://doi.org/10.1051/ps/2017003
- PDF (11.47 MB)
- References
Further refinement of self-normalized Cramér-type moderate deviations

Hailin Sang and Lin Ge

ESAIM: PS, 21 (2017) 201-219

Published online: 19 October 2017

DOI: https://doi.org/10.1051/ps/2017010
- PDF (298.4 KB)
- References
Stability of Densities for Perturbed Diffusions and Markov Chains

Valentin Konakov, Anna Kozhina and Stéphane Menozzi

ESAIM: PS, 21 (2017) 88-112

Published online: 20 March 2017

DOI: https://doi.org/10.1051/ps/2016028
- PDF (403.3 KB)
- References
Estimating the conditional density by histogram type estimators and model selection

Mathieu Sart

ESAIM: PS, 21 (2017) 34-55

Published online: 09 March 2017

DOI: https://doi.org/10.1051/ps/2016026
- PDF (326.5 KB)
- References
Unbiased Monte Carlo estimate of stochastic differential equations expectations

Mahamadou Doumbia, Nadia Oudjane and Xavier Warin

ESAIM: PS, 21 (2017) 56-87

Published online: 09 March 2017

DOI: https://doi.org/10.1051/ps/2017001
- PDF (2.148 MB)
- References

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ESAIM: Probability and Statistics (ESAIM: P&S)

Central limit theorem for supercritical binary homogeneous Crump-Mode-Jagers processes

Minimax regression estimation for Poisson coprocess

Quasi-ergodicity for absorbing Markov processes via deviation inequality

L^p-Solutions of backward doubly stochastic differential equations with stochastic Lipschitz condition and p ∈ (1,2)

A note on upper-patched generators for Archimedean copulas

Further refinement of self-normalized Cramér-type moderate deviations

Stability of Densities for Perturbed Diffusions and Markov Chains

Estimating the conditional density by histogram type estimators and model selection

Unbiased Monte Carlo estimate of stochastic differential equations expectations

Theory of Classification: a Survey of Some Recent Advances

How many bins should be put in a regular histogram

Inference on overlap coefficients under the Weibull distribution: Equal shape parameter

The likelihood ratio test for general mixture models with or without structural parameter

Moderate Deviations for I.I.D. Random Variables

Theory of Classification: a Survey of Some Recent Advances

Moderate Deviations for I.I.D. Random Variables

How many bins should be put in a regular histogram

Inference on overlap coefficients under the Weibull distribution: Equal shape parameter

Analysis of the Rosenblatt process

Theory of Classification: a Survey of Some Recent Advances

Moderate Deviations for I.I.D. Random Variables

How many bins should be put in a regular histogram

Inference on overlap coefficients under the Weibull distribution: Equal shape parameter

A martingale control variate method for option pricing with stochastic volatility

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