Papers to Appear in Subsequent Issues

Kernel methods in machine learning

Correction Note: Strong invariance principles for sequential Bahadur-Kiefer and Vervaat error processes of long-range dependent processes

Statistical modelling of causal effects in continuous time

Pre-conditioning for feature selection and regression in high-dimensional problems

One-step Sparse Estimates in Nonconcave Penalized Likelihood Models

Rates of contraction of posterior distributions based on Gaussian process priors

Adaptive estimation of and oracle inequalities for probability densities and characteristic functions

Current status data with competing risks: consistency and rates of convergence of the MLE

Current status data with competing risks: limiting distribution of the MLE

Adaptive Goodness-of-Fit Tests based on Signed Ranks

Data-driven Sobolev tests of uniformity on compact Riemannian manifolds

Hurst exponent estimation of locally self-similar Gaussian processes using sample quantiles

Estimation for Almost Periodic Processes

A CLT for regularized sample covariance matrices

High Dimensional Classification Using Features Annealed Independence Rules

Multivariate spacings based on data depth: I. construction of nonparametric tolerance regions

Admissible Predictive Density Estimation

Composite Quantile Regression and The Oracle Model Selection Theory

Optimal Rank-based Tests for Homogeneity of Scatter

Adaptive Variance Function Estimation in Heteroscedastic Nonparametric Regression

The Distribution of Maxima of Approximately Gaussian Random Fields

Parametric Bootstrap Approximation to the Distribution of Eblup, and Related Prediction Intervals in Linear Mixed Models

Robust Nonparametric Estimation via Wavelet Median Regression

Limit Theorems for Weighted Samples with Applications to Sequential Monte Carlo Methods

A General Trimming Approach to Robust Cluster Analysis

Common Functional Principal Components

Fence methods for mixed model selection

Optimal Designs for Mixed Models in Experiments Based On Ordered Units

Semiparametric Detection of Significant Activation for Brain fMRI

The Sparsity and Bias of the Lasso Selection in High-dimensional Linear Regression

Multiscale Inference about a Density

Moments of Minors of Wishart Matrices

Higher Order Semiparametric Frequentist Inference with the Profile Sampler

Locally Adaptive Estimation of Evolutionary Wavelet Spectra

Asymptotic equivalence for nonparametric regression with multivariate and random design

Searching for a Trail of Evidence in a Maze

A Wavelet Whittle estimator of the memory parameter of a non-stationary Gaussian time series

On the Behrens-Fisher problem: a globally convergent algorithm and a finite-sample study of the Wald, LR and LM Tests

Dimension Reduction Based on Constrained Canonical Correlation and Variable Filtering

A multivariate central limit theorem for randomized orthogonal array sampling designs in computer experiments

Analysis of Variance, Coefficient of Determination, and F-Test for Local Polynomial Regression

An Algorithmic and a Geometric Characterization of Coarsening At Random

Confidence Bands in Nonparametric Time Series Regression

Estimation of Distributions, Moments and Quantiles in Deconvolution Problems

Adaptive Estimation of the Excess of a Distribution Function

General Frequentist Properties of the Posterior Profile Distribution

Choice of Neighbour Order in Nearest-Neighbour Classification

A Data-Driven Block Thresholding Approach to Wavelet Estimation

A class on Renyi information estimators for multidimensional densities

Stein estimation for the drift of Gaussian processes using the Malliavin calculus

Trimming and likelihood: Robust location and dispersion estimation in the elliptical model

Evaluation of Formal Posterior Distributions via Markov Chain Arguments

Residual Empirical Processes for Long and Short Memory Time Series

Profile-Kernel Likelihood Inference With Diverging Number of Parameters

Multiple Local Whittle Estimation in Stationary Systems

Learning by Mirror Averaging

Gibbs posterior for variable selection in high dimensional classification and data mining

Local Antithetic Sampling with Scrambled Nets

Tilted Euler characteristic densities for Central Limit random fields, with application to `bubbles'

Monte-Carlo maximum likelihood estimation for discretely observed diffusion processes

Inference for the limiting cluster size distribution of extreme values

Functional Deconvolution in a Periodic Setting

Quantile pyramids for Bayesian nonparametrics

Proportional hazards models with continuous marks

Extending the Scope of Empirical Likelihood

Multivariate Archimedean Copulas, D-monotone Functions and L1-norm Symmetric Distributions

Robustness of multiple testing procedures against dependence

Consistencies and Rates of Convergence of Jump-Penalized Least Squares Estimators

Operator norm consistent estimation of large dimensional sparse covariance matrices

Support points of locally optimal designs for nonlinear models

Statistical Inference for Semiparametric Varying-coefficient Partially Linear Models with Generated Regressors

Consistency of support vector machines for forecasting the evolution of an unknown ergodic dynamical system from observations with unknown noise

Smoothing Splines Estimators for Functional Linear Regression

Inference for Censored Quantile Regression Models in Longitudinal studies

Minimum Distance Regression Model Checking with Berkson Measurement Errors

Efficient estimation for homothetic shifted regression models

A note on the stationary bootstrap's variance

Testing for Jumps in a Discretely Observed Process

On the false discovery rate and an asymptotically optimal rejection curve

Robust Estimation for ARMA models

Likelihood ratio tests and singularities

Asymptotic Inference for Semiparametric Association Models

Discussion of "One-step sparse estimates in nonconcave penalized likelihood models (H. Zou and R. Li)

Who cares if it is a white cat or a black cat? Discussion of "One-step sparse estimates in nonconcave penalized likelihood models (H. Zou and R. Li)

Discussion of "One-step sparse estimates in nonconcave penalized likelihood models (H. Zou and R. Li)

Rejoinder: "One-step sparse estimates in nonconcave penalized likelihood models"

Gaussian model selection with an unknown variance

The pseudo-marginal approach for efficient Monte Carlo computations

Confidence Regions, Regularization and Non-Parametric Regression

A universal procedure for aggregating estimators

Improving SAMC Using Smoothing Methods: Theory and Applications

A Pseudo Empirical Likelihood Approach for Stratified Samples with Nonresponse

Estimating a concave distribution function from data corrupted with additive noise

SCAD-Penalized Regression in High-Dimensional Partially Linear Models

Spectrum estimation for large dimensional covariance matrices

Lasso-type Recovery of Sparse Representations for High-dimensional Data

Statistical eigen-inference from large Wishart matrices

The Composite Absolute Penalties Family for Grouped and Hierarchical Variable Selection

Empirical Likelihood for Estimating Equations with Missing Values

An adaptive step-down procedure with proven FDR control

The Formal Definition of Reference Priors

Propagation of Outliers in Multivariate Data

An RKHS Formulation of the Inverse Regression Dimension Reduction Problem

The maximum of the periodogram of stationary process

Differentiability Of T-Functionals Of Location And Scatter

The Chernoff lower bound for symmetric quantum hypothesis testing

Matrix representations and independencies in directed acyclic graphs

On surrogate loss functions and f-divergences

Asymptotics in response-adaptive designs generated by a two-color, randomly reinforced urn

A Nonmanipulable Test

Dimension reduction for non-elliptically distributed predictors

New Multi-sample Nonparametric Tests For Panel Count Data

Covariance Regularization by Thresholding

Asymptotics For Spherical Needlets

Change–Point Estimation Under Adaptive Sampling

Building and Using Semiparametric Tolerance Regions for Parametric Multinomial Models

Does Median Filtering Truly Preserve Edges Better Than Linear Filtering?

Multivariate Analysis and Jacobi Ensembles: Largest eigenvalue, Tracy Widom Limits and Rates of Convergence

Consistency of Bayesian Procedures for Variable Selection

Adaptative estimation for inverse problem. Propagation Approach

Consistency of restricted maximum likelihood estimators of principal components

Limit Distribution Theory for Maximum Likelihood Estimation of a Log-Concave Density

On nonparametric and semiparametric testing for multivariate time series

Nonparametric estimation of composite functions

Multiscale local change point detection with applications to Value-at-Risk

Nonlinear Sequential Designs for Logistic Item Response Theory Models with Applications to Computerized Adaptive Tests

Minimal sufficient causation and directed acyclic graphs

Case-Control Survival Analysis With a General Semiparametric Shared Frailty Model - A Pseudo Full Likelihood Approach

A new multiple testing method in the dependent case

On generalized false discovery rate

Finite Sample Convergence Results for Principal Component Analysis: A matrix perturbation approach

Flexible Covariance Estimation in Graphical Models

Simultaneous analysis of Lasso and Dantzig selector

Sparse Recovery in Convex Hulls via Entropy Penalization

On-line predictive linear regression

Fast learning rates in statistical inference through aggregation