JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Activity Details


174 Mon, 7/30/2012, 10:30 AM - 12:20 PM CC-Room 30B
Big Data: Strategies for Large P, Large N, or Massive Data — Contributed Papers
Section on Statistical Computing , Section on Statistical Education , Committee on Applied Statisticians , Section on Statistical Learning and Data Mining
Chair(s): Peng Zeng, Auburn University
10:35 AM Parallel External Memory Algorithms Applied to Generalized Linear Models Lee Edlefsen, Revolution Analytics
10:50 AM Approximate Centroid Inference for Complex Graphical Models Hunter Glanz, Boston University ; Luis Carvalho, Boston University
11:05 AM Limited-Information Statistics When the Number of Variables Is Large Mark Reiser, Arizona State University
11:20 AM A Simple Distribution-Free Algorithm for Generating Simulated High-Dimensional Correlated Data with an Autoregressive Structure Andres Azuero, The University of Alabama at Birmingham ; Hemant K Tiwari, The University of Alabama at Birmingham ; David T Redden, The University of Alabama at Birmingham
11:35 AM Variable Selection in Sparse Ultra High-Dimensional Additive Models with Continuous or Discrete Response Variable Girly Ramirez, Kansas State University ; Haiyan Wang, Kansas State University
11:50 AM Model-Based Clustering Analysis of Large Climate Simulation Data Sets Wei-Chen Chen, Oak Ridge National Laboratory ; George Ostrouchov, Oak Ridge National Laboratory ; David Pugmire, Oak Ridge National Laboratory ; Mr Prabhat, Lawrence Berkeley National Laboratory ; Michael Wehner, Lawrence Berkeley National Laboratory
12:05 PM Computation of Order Statistics for Very Large and Distributed Data Damir Spisic, IBM SPSS Predictive Analytics ; Graham J. Wills, IBM SPSS Predictive Analytics ; Fan Li, IBM SPSS Predictive Analytics



2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.