Bernoulli

Volume 10.

(as bibtex)

52 references.

Articles

• 1-24. Counting process intensity estimation by orthogonal wavelet methods
  Patil, Prakash N., Wood, Andrew T.A.
• 1011-1037. Asymptotically optimal model selection method with right censored outcomes
  Keleş, Sündüz, Van Der Laan, Mark, Dudoit, Sandrine, Keles, Sündüz
• 1039-1051. Model selection for Gaussian regression with random design
  Birgé, Lucien
• 1053-1105. Regression in random design and warped wavelets
  Kerkyacharian, Gérard, Picard, Dominique
• 121-163. Slow, fast and arbitrary growth conditions for renewal-reward processes when both the renewals and the rewards are heavy-tailed
  Pipiras, Vladas, Taqqu, Murad S., Levy, Joshua B.
• 165-186. A stochastic wave equation in dimension 3: Smoothness of the law
  Quer-Sardanyons, Lluís, Sanz-solé, Marta
• 187-220. On minimax density estimation on \mathbb{R}}
  Lambert-Lacroix, Sophie, Juditsky, Anatoli
• 187-220. On minimax density estimation on $\Re$
  Juditsky, Anatoli, Lambert-Lacroix, Sophie
• 221-250. Berry-Esseen and central limit theorems for serial rank statistics via graphs
  Turova, Tatyana S.
• 25-47. Aggregating regression procedures to improve performance
  Yang, Yuhong
• 251-280. Bivariate tail estimation: dependence in asymptotic independence
  Draisma, Gerrit, Drees, Holger, Ferreira, Ana, de Haan, Laurens
• 281-312. Transition density estimation for stochastic differential equations via forward-reverse representations
  Milstein, Grigori N., Schoenmakers, John G.M., Spokoiny, Vladimir
• 313-325. Martingale-type stochastic calculus for anticipating integral processes
  Tudor, Ciprian A.
• 327-355. Stable limits of sums of bounded functions of long-memory moving averages with finite variance
  Surgailis , Donatas
• 357-373. On roughness indices for fractional fields
  Benassi, Albert, Cohen, Serge, Istas, Jacques
• 377-396. Laslett's line segment problem
  Van Zwet, Erik W.
• 397-419. Asymptotics for the Tukey depth process, with an application to a multivaiate trimmed mean
  Massé, Jean-Claude
• 397-419. Asymptotics for the Tukey depth process, with an application to a multivariate trimmed mean
  Massé, Jean-Claude
• 421-446. Likelihood functions based on parameter-dependent functions
  Severini, Thomas A.
• 447-463. Asymptotic normality of urn models for clinical trials with delayed response
  Zhang, Li-Xin, Hu, Feifang
• 447-463. Asymptotic normality of urn models fo clinical trials with delayed response
  Hu, Feifang, Zhang, Li-Xin
• 465-501. Saddlepoint approximations to the trimmed mean
  Helmers, Roelof, Jing, Bing-Yi, Qin, Gengsheng, Zhou, Wang
• 49-78. Estimation and testing in a partial linear regression model under long-memory dependence
  Aneiros-Pérez, Germán, González-Manteiga, Wenceslao, Vieu, Philippe
• 503-548. Rate of convergence in probability to the Marchenko-Pastur law
  Götze, Friedrich, Tikhomirov, Alexander
• 549-564. Stability of the tail Markov chain and the evaluation of improper priors for an exponential rate parameter
  Hobert, James P., Marchev, Dobrin, Schweinsberg, Jason
• 565-582. Nonparametric independent component analysis
  Samarov, Alexander, Tsybakov, Alexandre
• 583-604. Semiparametric density estimation under a two-sample density ratio model
  Cheng, K.F., Chu, C.K.
• 605-637. Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes
  Francq, Christian, Zakoïan, Jean-Michel
• 639-649. On the global geometry of parametric models and information recovery
  Marriott, Paul, Vos, Paul
• 651-663. Extending Doob's consistency theorem to nonparametric densities
  Lijoi, Antonio, Prünster, Igor, Walker, Stephen G.
• 665-683. On local estimates and the Stein method
  Čekanavičius, Vydas
• 685-700. The Matsumoto-Yor property on trees
  Massam, Hélène, Wesołowski, Jacek
• 701-720. Random scale perturbation of an AR(1) process and its properties as a nonlinear explicit filter
  Genon-Catalot, Valentine, Kessler, Mathieu
• 721-752. The law of the iterated logarithm for the integrated squared deviation of a kernel density estimator
  Giné, Evarist, Mason, David M.
• 755-782. Transportation of measure, Young diagrams and random matrices
  Blower, Gordon
• 783-827. Solutions of stochastic partial differential equations considered as Dirichlet processes
  Laurent, Denis
• 79-96. The Bernoulli sieve
  Gnedin, Alexander V.
• 829-845. Large deviations for global maxima of independent superadditive processes with negative drift and an application to optimal sequence alignments
  Grossmann, Steffen, Yakir, Benjamin
• 847-860. Weak convergence of empirical copula processes
  Fermanian, Jean-David, Radulović, Dragan, Wegkamp, Marten
• 861-872. Dutch book against some 'objective' priors
  Eaton, Morris L., Freedman, David A.
• 861-872. Dutch book against some `objective' priors
  Freedman, David A., Eaton, Morris L.
• 873-888. Asymptotically exact minimax estimation in sup-norm for anisotropic Hölder classes
  Bertin, Karine
• 889-917. Functional convergence and optimality of plug-in estimators for stationary densities of moving average processes
  Schick, Anton, Wefelmeyer, Wolfgang
• 919-938. Nonparametric methods of inference for finite-state, inhomogeneous Markov processes
  Hall, Peter, Bura, Efstathia
• 939-943. High-dimensional data: p >> n in mathematical statistics and bio-medical applications
  Van Houwelingen, Hans C., Van De Geer, Sara A.
• 943-949. Intensity-dependent normalization in microarray analysis: A note of concern
  Ting Lee, Mei-Ling, Whitmore, George A.
• 951-969. A nested unsupervised approach to identifying novel molecular subtypes
  Garrett, Elizabeth S., Parmigiani, Giovanni
• 97-120. On multidimensional Ornstein-Uhlenbeck processes driven by a general Lévy process
  Masuda, Hiroki
• 971-988. Persistence in high-dimensional linear predictor selection and the virtue of overparametrization
  Ritov, Ya'Acov, Greenshtein, Eitan
• 971-988. Persistence in high-dimensional linear preditor selection and the virtue of overparametrization
  Greenshtein, Eitan, Ritov, Ya'acov
• 989-1010. Some theory for Fisher's linear discriminant function, 'naive Bayes', and some alternatives when there are many more variables than observations
  Bickel, Peter J., Levina, Elizaveta
• 989-1010. Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
  Levina, Elizaveta, Bickel, Peter J.