Publications de Jérôme Dedecker

Publications et rapports de recherche

Revues internationales

A central limit theorem for stationary random fields, J. Dedecker, Probability Theory and Related Fields 110 (1998) 397-426.
On the functional central limit theorem for stationary processes, J. Dedecker and Emmanuel Rio, Annales de l'Institut Henri Poncaré, Probabilités et Statistiques 36 (2000) 1-34.
Exponential inequalities and functional central limit theorem for random fields, J. Dedecker, ESAIM Probability and Statistics 5 (2001) 77-104.
Necessary and sufficient conditions for the conditional central limit theorem, J. Dedecker and F. Merlevède, Annals of Probability 30 (2002) 1044-1081.
A new covariance inequality and applications, J. Dedecker and P. Doukhan, Stochastic Processes and their Applications 106 (2003) 63-80.
The conditional central limit theorem in Hilbert spaces, J. Dedecker and F. Merlevède, Stochastic Processes and their Applications 108 (2003) 229-262.
Coupling for τ-dependent sequences and applications, J. Dedecker and C. Prieur, Journal of Theoretical Probability 17 (2004) 861-885.
Conditional convergence to infinitely divisible distributions with finite variance, J. Dedecker and S. Louhichi, Stochastic Processes and their Applications 115 (2005) 737-768.
Convergence to infinitely divisible distributions with finite variance for some weakly dependent sequences, J. Dedecker and S. Louhichi, ESAIM Probability and Statistics 9 (2005) 38-73.
New dependence coefficients. Examples and applications to statistics, J. Dedecker and C. Prieur, Probability Theory and Related Fields 132 (2005) 203-236.
Inequalities for partial sums of Hilbert valued dependent sequences and applications, J. Dedecker and F. Merlevède, Mathematical Methods of Statistics 15 (2006) 176-206.
An empirical central limit theorem for dependent sequences, J. Dedecker and C. Prieur, Stochastic Processes and their Applications 117 (2007) 121-142.
The empirical distribution function for dependent variables: asymptotic and non asymptotic results in Lp, J. Dedecker and F. Merlevède, ESAIM Probability and Statistics 11 (2007) 102-114.
On the weak invariance principle for non adapted sequences under projective criteria, J. Dedecker, F. Merlevède and D. Volny, Journal of Theoretical Probability 20 (2007) 971-1004.
Convergence rates in the law of large numbers for Banach valued dependent variables, J. Dedecker and F. Merlevède, Teor. Veroyatnost. i Primenen 52 (2007) 562-587.
On mean central limit theorems for stationary sequences, J. Dedecker and E. Rio, Annales de l'Institut Henri Poncaré, Probabilités et Statistiques 44 (2008) 693-726.
Adaptive density deconvolution with dependent inputs, F. Comte, J. Dedecker and M-L. Taupin, Mathematical Methods of Statistics 17 (2008) 87-112.
Adaptive density estimation for general ARCH models, F. Comte, J. Dedecker and M-L. Taupin, Econometric Theory 24 (2008) 1628-1662.
Some unbounded functions of intermittent maps for which the central limit theorem holds, J. Dedecker and C. Prieur, Alea 5 (2009) 29-45.
Moderate deviations for stationary sequences of bounded random variables, J. Dedecker, F. Merlevède, M. Peligrad and S. Utev, Annales de l'I. H. P., Probabilités et Statistiques 45(2009) 453-476.
Rates of convergence for minimal distances in the central limit theorem under projective criteria, J. Dedecker, F. Merlevède and E. Rio, Electronic Journal of Probability 35 (2009) 978-1011.
An empirical central limit theorem for intermittent maps, J. Dedecker, Probability Theory and Related Fields 148 (2010) 177-195.
Some almost sure results for unbounded functions of intermittent maps and their associated Markov chains, J. Dedecker, S. Gouëzel and F. Merlevède, Annales de l'I. H. P., Probabilités et Statistiques 46 (2010) 796-821.
Invariance principles for linear processes with application to isotonic regression, J. Dedecker, F. Merlevède and M. Peligrad, Bernoulli 17 (2011) 88-113.
Rates of convergence in the central limit theorem for linear statistics of martingale differences, J. Dedecker and F. Merlevède, Stochastic Processes and their Applications 121 (2011) 1013-1043.
Deconvolution for the Wasserstein metric and geometric inference, C. Caillerie, F. Chazal, J. Dedecker and B. Michel, Electronic journal of statistics 5 (2011) 1394-1423.
The almost sure invariance principle for unbounded functions of expanding maps, J. Dedecker, S. Gouëzel and F. Merlevède, Alea 9 (2012) 141-163.
Rates of convergence in the strong invariance principle under projective criteria, J. Dedecker, P. Doukhan and F. Merlevède, Electronic Journal of Probability 17 (2012) 1-31.
Minimax rates of convergence for Wasserstein deconvolution with supersmooth errors in any dimension, J. Dedecker and B. Michel, Journal of multivariate Analysis 122 (2013) 278-291.
Empirical central limit theorems for ergodic automorphisms of the torus, J. Dedecker, F. Merlevède and F. Pène, Alea 10 (2013) 779-814.
On strong approximation for the empirical process of stationary sequences, J. Dedecker, F. Merlevède and E. Rio, Annals of Probability 41 (2013) 3658-3696.
Strong approximation of the empirical distribution function for absolutely regular sequences, J. Dedecker, F. Merlevède and E. Rio, Electronic Journal of Probability 19 (2014) 1-56.
A quenched weak invariance principle, J. Dedecker, F. Merlevède and M. Peligrad, Annales de l'I. H. P., Probabilités et Statistiques 3 (2014) 872-898.
Rates in the strong invariance principle for ergodic automorphisms of the torus, J. Dedecker, F. Merlevède and F. Pène, Stochastics and Dynamics 14 (2014).
Estimation in autoregressive models with measurement error, J. Dedecker, A. Samson and M.-L. Taupin, ESAIM Probability and Statistics 18 (2014) 227-307.
Deviation inequalities for separately Lipschitz functionals of iterated random functions, J. Dedecker and X. Fan, Stochastic Processes and their Applications 125 (2015) 60-90.
Improved bounds for Wasserstein deconvolution with ordinary smooth error in dimension 1, J. Dedecker, A. Fischer and B. Michel, Electronic Journal of Statistics 9 (2015) 234-26.
Weak convergence of the empirical process of intermittent maps in L² under long-range dependence, J. Dedecker, H. G. Dehling and M. S. Taqqu, Stochastics and Dynamics 15 (2015) 29 pages.
Moment bounds for dependent sequences in smooth Banach spaces, J. Dedecker and F. Merlevède, Stochastic Processes and their Applications 125 (2015) 3401–3429.
Subgaussian concentration inequalities for geometrically ergodic Markov chains, J. Dedecker and S. Gouëzel, Electronic Communication in probability 20 (2015) 12 pages.
A deviation bound for α-dependent sequences with applications to intermittent maps, J. Dedecker and F. Merlevède, Stochastics and Dynamics 17 (2017) 27 pages.
Behavior of the Wasserstein distance between the empirical and the marginal distributions of stationary α-dependent sequences, J. Dedecker and F. Merlevède, Bernoulli 23 (2017) 2083–2127.
Density estimation for β-dependant sequences, J. Dedecker and F. Merlevède, Electronic Journal of Statistics 11 (2017) 981-1021.
The Mann–Whitney U-statistic for α-dependent sequences, J. Dedecker and G. Saulière, Mathematical Methods of Statistics 26 (2017) 111–133.

Proceedings

Maximal inequalities and empirical central limit theorems, J. Dedecker and S. Louhichi, Empirical Process Techniques for Dependent Data (2002) 137-159. Dehling, Mikosch and Sorensen editors, Birkhauser.
Parametrized Kantorovich-Rubinstein theorem and application to the coupling of random variables, J. Dedecker, C. Prieur and P. Raynaud De Fitte, Dependence in Probability and Statistics, Lectures Notes in Statistics 187 (2006) 105-121.
Inégalités de Hoeffding et théorème limite central pour les fonctions peu régulières de chaînes de Markov non irréductibles, J. Dedecker, numéro spécial des Annales de l'ISUP 52 (2008) 39-46.
Weak invariance principle and exponential bounds for some special functions of intermittent maps, J. Dedecker and F. Merlevède, High dimensional probability 5 (2009) 60-72.
On the almost sure invariance principle for stationary sequences of Hilbert-valued random variables, J. Dedecker and F. Merlevède, Dependence in probability, analysis and number theory (2010) 157-175
Rates of convergence in the strong invariance principle for non adapted sequences. Application to ergodic automorphisms of the torus, J. Dedecker, F. Merlevède and F. Pène, High dimensional probabilty 6 (2013) 113-138.
Limit theorems and inequalities via martingale methods, J.-R. Chazottes, C. Cuny, J. Dedecker, X. Fan and S. Lemler, ESAIM : Proceedings 44 (2014) 177-196.
A functional central limit theorem for fields of commuting transformations via martingale approximation, C. Cuny, J. Dedecker and D. Volný, Zapiski Nauchnyh Seminarov POMI 441 (2015), dedicated to the memory of M. Gordin.

Rapports de recherche

Limit theorems for the left random walk on GL_d (R), C. Cuny, J. Dedecker and C. Jan.
Large and moderate deviations for the left random walk on GL_d (R), C. Cuny, J. Dedecker and F. Merlevède.
Large and moderate deviations for bounded functions of slowly mixing Markov chains, J. Dedecker, S. Gouëzel and F. Merlevède.
On the Komlós, Major and Tusnády strong approximation for some classes of random iterates, C. Cuny, J. Dedecker and F. Merlevède.

Comptes rendus de l'académie des sciences de Paris

Inégalités de covariance, J. Dedecker, Comptes rendus de l'académie des sciences de Paris 339 (2004) 503-506.
On the optimality of McLeish's conditions for the central limit theorem, J. Dedecker, Comptes rendus de l'académie des sciences de Paris, 353 (2015) 557-561.

Lecture notes in statistics

Weak dependence, with examples and applications, J. Dedecker, P Doukhan, G. Lang, J.-R. Leon, S. Louhichi and C. Prieur, Lecture notes in statistics 190, 318 p. Springer.