Statistics and Its Interface

Volume 9 (2016)

Number 4

Special Issue on Statistical and Computational Theory and Methodology for Big Data

Guest Editors: Ming-Hui Chen (University of Connecticut); Radu V. Craiu (University of Toronto); Faming Liang (University of Florida); and Chuanhai Liu (Purdue University)

Contents

Preface

pp. 397-398

Statistical methods and computing for big data

Chun Wang, Ming-Hui Chen, Elizabeth Schifano, Jing Wu, and Jun Yan

pp. 399-414

Iterative subsampling in solution path clustering of noisy big data

Yuliya Marchetti and Qing Zhou

pp. 415-431

Smoothing spline ANOVA for super-large samples: scalable computation via rounding parameters

Nathaniel E. Helwig and Ping Ma

pp. 433-444

Direct regression modelling of high-order moments in big data

Ruibin Xi and Nan Lin

pp. 445-452

A split-and-merge approach for singular value decomposition of large-scale matrices

Faming Liang, Runmin Shi, and Qianxing Mo

pp. 453-459

High-dimensional covariance estimation under the presence of outliers

Hsin-Cheng Huang and Thomas C. M. Lee

pp. 461-468

Model diagnostics in reduced-rank estimation

Kun Chen

pp. 469-484

Generative modeling of convolutional neural networks

Jifeng Dai, Yang Lu, and Ying Nian Wu

pp. 485-496

Embarrassingly parallel sequential Markov-chain Monte Carlo for large sets of time series

Roberto Casarin, Radu V. Craiu, and Fabrizio Leisen

pp. 497-508

BIG-SIR: a Sliced Inverse Regression approach for massive data

Benoit Liquet and Jerome Saracco

pp. 509-520

Sparse generalized principal component analysis for large-scale applications beyond Gaussianity

Qiaoya Zhang and Yiyuan She

pp. 521-533

Preprocessing solar images while preserving their latent structure

Nathan M. Stein, David A. van Dyk, and Vinay L. Kashyap

pp. 535-551

Indices

Contents of Volume 9