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Papers to Appear in Subsequent Issues

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

Miklos Csorgo, Barbara Szyszkowicz, and Lihong Wang

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

Alexander J. McNeil, and Johanna Neslehova

Efficient estimation for homothetic shifted regression models

Myriam Vimond

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)

Xiao-Li Meng

Confidence Regions, Regularization and Non-Parametric Regression

Patrick Laurie Davies, Arne Kovac, and Monika Meise

Improving SAMC Using Smoothing Methods: Theory and Applications

Faming Liang

The Composite Absolute Penalties Family for Grouped and Hierarchical Variable Selection

Peng Zhao, Guilherme Veiga da Rocha, and Bin Yu

The maximum of the periodogram of stationary process

Lin Zhengyan and Liu Weidong

Building and Using Semiparametric Tolerance Regions for Parametric Multinomial Models

Jiawei Liu and Bruce G Lindsay

Adaptative estimation for inverse problem. Propagation Approach

Vladimir Spokoiny and Céline Vial

On nonparametric and semiparametric testing for multivariate time series

Yoshihiro Yajima and Yasumasa Matsuda

Markov Equivalence for Ancestral Graphs

Ayesha Ali, Thomas Stuart Richardson, and Peter Spirtes

Goodness-of-fit Tests for high-dimensional Gaussian linear models

Nicolas Verzelen, and Fanny Villers

Local Linear Quantile Estimation for Non-stationary Time Series

Zhou Zhou, and Wei Biao Wu

Consistency of a Recursive Estimate of Mixing Distributions

Surya Tokdar, Ryan Martin, and Jayanta Ghosh

Estimating the Degree of Activity of Jumps in High Frequency Financial Data

Yacine Ait-Sahalia and Jean Jacod

Functional Linear Regression That's Interpretable

Gareth James, Jing Wang and Ji Zhu

Estimating linear functionals in nonlinear regression with responses missing at random

Ursula U. Mueller

On Asymptotically Optimal Tests Under Loss of Identifiability In Semiparametric Models

Rui Song, Michael R Kosorok, and Jason P Fine

Existence and Construction of Randomization Defining Contrast Subspaces for Regular Factorial Designs

Pritam Ranjan, Derek Bingham, and Angela Dean

Asymptotic Equivalence of Empirical Likelihood and Bayesian Map

Marian Grendar, and George G. Judge

High Dimensional Variable Selection

Larry Wasserman, and Kathryn Roeder

Consistent Estimates of Deformed Isotropic Gaussian Random Fields on the Plane

Ethan Berger Anderes, and Sourav Chatterjee

The spectrum of kernel random matrices

Noureddine El Karoui

Bayesian Frequentist Hybrid Inference

Ao Yuan

Introduction to AS Special Issue on Random Matrices

Peter J Bickel

Hypothesis test for normal mixture models: the EM approach

Jiahua Chen, and Li Pengfei

Deconvolution with unknown error distribution

Jan Johannes

Near-ideal model selection by L1 minimization

Emmanuel Jean Candes, and Yaniv Plan

Nonparametric Estimation by Convex Programming

Anatoli B. Juditsky, and Arkadi S. Nemirovski

Efficient Randomized Adaptive Designs

Feifang Hu, Li-xin Zhang, and Xuming He

Quarter-Fraction Factorial Designs Constructed Via Quaternary Codes

Frederick K. H. Phoa, and Hongquan Xu

Asymptotic Theory for the Semiparametric Accelerated Failure Time Model with Missing Data

Bin Nan, John D. Kalbfleisch, and Menggang Yu

Asymptotic Normality of a Nonparametric Estimator of Sample Coverage

Cun-Hui Zhang and Zhiyi Zhang

Some Sharp Performance Bounds for Least Squares Regression with L1 Regularization

Tong Zhang

Conditional predictive inference post model selection

Hannes Leeb

Adaptive Hausdorff Estimation of Density Level Sets

Aarti Singh, Clayton Scott, and Robert Nowak

A Semiparametric Model for Cluster Data

Wenyang Zhang, Jianqing Fan, and Yan Sun

Estimating the Gumbel Scale Parameter for Local Alignment of Random Sequences by Importance Sampling with Stopping Times

Yonil Park, Sergey Sheetlin, and John L. Spouge

High-dimensional analysis of semidefinite relaxations for sparse principal components

Arash A. Amini and Martin J. Wainwright

Properties and Refinements of the Fused Lasso

Alessandro Rinaldo

Improved kernel estimation of copulas: weak convergence and goodness-of-fit testing

Marek Omelka, Irene Maria Gijbels, and Noël Veraverbeke

Non-asymptotic resampling-based confidence regions and multiple tests in high dimension

Sylvain Arlot, Gilles Blanchard, and Etienne Roquain

Some non-asymptotic results on resampling in high dimension, II: Multiple tests

Sylvain Arlot, Gilles Blanchard, and Etienne Roquain

A conjugate prior for discrete hierarchical loglinear models

Helene Menexia Massam, Jinnan Liu, and Adrian Dobra

Some Results on 2n-m Designs of Resolution IV With (Weak) Minimum Aberration

Hegang Chen, and Ching-Shui Cheng

On the path density of a gradient field

Christopher R Genovese, Marco Pacifico-Perone, Isabella Verdinelli, and Larry Wasserman

Rank-based inference for extreme-value copulas

Christian Genest and Johan Segers

On Random Tomography with Unobservable Projection Angles

Victor Michael Panaretos

Asymptotic normality of the Quasi Maximum Likelihood Estimator

Jean-Marc Bardet and Olivier Wintenberger

Estimation of trend in state-space models: asymptotic mean square error and rate of c

Prabir Burman

Fixed-domain Asymptotic Properties of Tapered Maximum Likelihood Estimators

Juan Du, Hao Zhang, and Vidyadhar S Mandrekar

Maximum empirical likelihood estimation of the spectral measure of an extreme value distribution

John H. J. Einmahl and Johan Segers

Adaptive Bayesian estimation using a Gaussian random field with inverse Gamma bandwidth

Aad van der Vaart and Harry van Zanten

Contour Projected Dimension Reduction

Ronghua Luo, Hansheng Wang, Chih-Ling Tsai

Goodness-of-fit problem for errors in non-parametric regression: distribution free approach

Estate V. Khmaladze and Hira L. Koul

Symptotic Equivalence and Adaptive Estimation for Robust Nonparametric Regression

Tony Cai and Harrison Zhou

Adaptive density estimation for directional data using needlets

Paolo Baldi, Kerkyacharian Gerard, Domenico Marinucci, and Dominique Picard

A Unified Approach to Model Selection and Sparse Recovery Using Regularized Least Squares

Jinchi Lv and Yingying Fan

Wavelet regression in random design with heteroscedastic dependent errors

Rafal Kulik and Marc Raimondo

Estimating high-dimensional intervention effects from observational data

Marloes H. Maathuis, Markus Kalisch, and Peter Bühlmann

Estimation of Functional Derivatives

Peter Hall, Hans-Georg Müller, and Fang Yao

Maximum Lq-Likelihood Estimation

Davide Ferrari and Yuhong Yang

A Maximum Likelihood Method for the Incidental Parameter

Marcelo J. Moreira

Identifiability of latent class models with many observed variables

Elizabeth S. Allman, Catherine Matias, and John A. Rhodes

Construction of Nested Space-Filling Designs

Peter Z. G. Qian, Mingyao Ai, and Jeff C. F. Wu

High-Dimensional Ising Model Selection Using L1 Regularized Logistic Regression

Pradeep Ravikumar, Martin J. Wainwright, and John D. Lafferty

High-Dimensional Additive Modeling

Lukas Meier, Sara van de Geer, and Peter Bühlmann

Asymptotic theory of semiparametric Z-estimators for stochastic processes, with applications to ergodic diffusions and time series

Yoichi Nishiyama

Corrections to LRT on Large Dimensional Covariance Matrix by RMT

Zhidong Bai, Dandan Jiang, J. Yao, and Shurong Zheng

Quantile Regression in Partially Linear Varying Coefficient Models

Huixia Judy Wang and Zhongyi Zhu

Optimal Rates of Convergence for Estimating the Null Density and Proportion of Non-Null Effects in Large-Scale Multiple Testing

Tony Cai and Jiashun Jin

Karl Pearson's Meta-Analysis Revisited

Art B Owen

Specification testing in nonlinear and nonstationary time series regression

Dag Bjarne Tjostheim, Jiti Gao, Maxwell King, and Zudi Lu

Using the bootstrap to quantify the authority of an empirical ranking

Peter Hall and Hugh Miller

Data spetrocopy: eigenspace of convolution operators and clustering

Tao Shi, Mikhail Belkin, and Bin Yu

Detection of Spatial Clustering with Average Likelihood Ratio Test Statistic

Hock Peng Chan

Inference for stochastic volatility models using time change transformations

Konstantinos Kalogeropoulos, Gareth O. Roberts, and Petros Dellaportas

Rates of convergence for the posterior distributions of mixtures of betas and adaptive nonparamatric estimation of the density

Judith Rousseau

Testing Conditional Independence via Rosenblatt Transforms

Kyungchul Song

Asymptotic equivalence of spectral density estimation and Gaussian white noise

Georgi K. Golubev, Michael Nussbaum, and Harrison H. Zhou

Nonlinear Principal Components and Long-run Implications of Multivariate Diffusions

Lars Peter Hansen, Xiaohong Chen, and Jose Scheinkman

Break detection in the covariance structure of multivariate time series

Alexander Aue, Siegfried Hörmann, Lajos Horváth, Matthew Reimherr

A geometric characterization of c-optimal designs for heteroscedastic regression

Holger Dette and Tim Holland-Letz

PCA consistency in high dimension, low sample size context

Sungkyu Jung and J. S. Marron

Globally optimal parameter estimates for nonlinear diffusions

Aleksandar Mijatovic and Paul Schneider

Subspace estimation algorithms for hidden Markov models: Algorithms and consistency

Sofia Andersson and Tobias Rydén

Estimation for a partial-linear single-index model

Lixing Zhu, Jane-Ling Wang, Liu Gen Xue, and Yun Sam Chong

Local quasi-likelihood with a parametric guide

Jianqing Fan, Yichao Wu, and Yang Feng

Bayesian Analysis in Moment Inequality Models

Yuan Liao and Wenxin Jiang

Spectral estimation of the fractional order of a Levy process

Denis Belomestny

A Two Sample Test for High Dimensional Data with Applications to Gene-set Testing

Song X Chen and Ying Li Qin

Decomposition Tables for Multitiered Experiments

Chris J. Brien and R. A. Bailey

Asymptotic Inference for High dimensional data

Anand Vidyashankar and Jim Kuelbs

Efficient Estimation of Copula-Based Semiparametric Markov Models

Xiaohong Chen, Wei Wu, and Yanping Yi

Sparsistency and Rates of Convergence in Large Covariance Matrices Estimation

Clifford Lam and Jianqing Fan

Maximum smoothed likelihood estimation and sommthed likelihood estimation in the current status model

Piet Groeneboom, Geurt Jongbloed, and Birgit Witte

Edgeworth expansions for studentized statistics under weak dependence

Soumendra N Lahiri

Multivariate Quantiles and Multiple-Output Regression Quantiles: From L1 Optimization to Halfspace Depth

Marc Hallin, Davy Paindaveine, and Miroslav Siman

Asymptotic efficiency and finite-sample properties of the generalized profiling estimation of the parameters in ordinary differential equations

Xin Qi and Hongyu Zhao

On the consistent separation of scale and variance for Gaussian random fields

Ethan Berger Anderes

Empirical risk minimization in inverse problems

Jussi Klemela and Enno Mammen

Invariant P-values for Model Checking and Checking for Prior-Data Conflict

Michael John Evans and Gu Ho Jang

Regularization in Kernel Learning

Joseph Neeman and Shahar Mendelson

Nearly Unbiased Variable Selection Under Minimax Concave Penalty

Cun-Hui Zhang

Vast Volatility Matrix Estimation for High-Frequency Financial Data

Yazhen Wang and Jian Zou

Estimation in Dirichlet Random Effects

George Casella, Minjung Kyung, and Jeff Gill
 
   
 
 

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