Associate Professor
in Econometrics and Statistics
Veronika.Rockova@ChicagoBooth.edu
I am Associate
Professor in
Econometrics and
Statistics and James S. Kemper Foundation Faculty Scholar at the
University of Chicago
Booth School of
Business.
My work
brings together
statistical
methodology, theory
and computation to
develop
high-performance tools
for analyzing large
datasets.
C++ written R package implementing an EM
algorithm for Bayesian variable selection described
in Rockova and George (2014). The software is made available as is, and no warranty -
about the software, its performance or its conformity to any
specification - is given or implied. Please email me with
comments
and suggestions.
The package can be installed via R CMD BUILD and R CMD INSTALL from a local R library directory.
C written R package implementing coordinate-wise optimization for Spike-and-Slab LASSO priors in linear regression (Rockova and George (2015)). Spike-and-Slab LASSO is a spike-and-slab refinement of the LASSO procedure, using a mixture of Laplace priors indexed by lambda0 (spike) and lambda1 (slab). The SSLASSO procedure fits coefficients paths for Spike-and-Slab LASSO-penalized linear regression models over a grid of values for the regularization parameter lambda_0.
R code for implementing rotations to sparsity in
high-dimensional factor models (Rockova
and George (2015)). FACTOR ROTATE is a unified Bayesian approach that incorporates factor rotations within the model fitting process, greatly enhancing the effectiveness of sparsity inducing priors. These automatic transformations are embedded within a new PXL-EM algorithm, a Bayesian variant of parameter-expanded EM for fast posterior mode detection.
Seonghyun is a Senior Research Professional in Econometrics and
Statistics
at
the
University
of
Chicago,
Booth
School
of
Business. Seonghyun
Jeong received his Ph.D. at North Carolina State University in the Department of Statistics under the guidance of Dr. Subhashis Ghoshal. He also obtained his M.A. and B.A. in Statistics from Yonsei University in Seoul, Korea. His research interests include Bayesian asymptotic theories, high- and infinite-dimensional inference, and nonparametric Bayes.
Enakshi is a
4th
year
PhD
Student at the Department of Statistics at the University
of
Chicago. She
received
BStat
and
MStat
degrees
from
the
Indian
Statistical
Institute
in
Kolkata,
India. Her
research
interests
primarily
include
Bayesian
Statistics,
Factor
Analysis,
Nonparametric
and
High
Dimensional
Statistical
methods
and
Time
Series
Analysis.
Yi is a 3rd year PhD Student in the Department of Statistics
at
the
University
of
Chicago.
Yi
obtained
his
undergraduate
degree
at
the
Imperial
College
London
and
later
a
master
degree
in
statistics
from
Stanford. Yi
is
deeply
interested
in
Bayesian Methods and application of Bayesian Statistics into different
fields
such
as
genetics
and
epidemiology. In his free time, Yi likes to watch documentaries about history and Nature.
Lizhen is a 3rd year PhD Student in the Department of Statistics
at
the
University
of
Chicago. Lizhen obtained her undergraduate degree at Zhejiang
University, China. Her research interests primarily include Bayesian methods with a
particular
emphasis
on
Bayesian computation and model selection.
Qing is a 3rd year PhD Student in the Department of Statistics
at
the
University
of
Chicago. Qing received his Bachelor’s degree in Pure and Applied Mathematics from Tsinghua University. His research interests include: Nonparametric Bayesian Method, Causal Inference, Computer Vision, Deep Generative Model, Invertible Neural Networks.
Yuexi is a 2nd year PhD student in Econometrics and
Statistics at Booth.
Yuexi received her master degree in Statistics at the University of
Chicago. Her research interests include Bayesian statistics and
machine learning. Prior to UChicago, she obtained a Bachelor’s degree
in Mathematics and Applied Mathematics from Zhejiang University
(China).
Tutorials: Google developer ,
Princeton , TryR
code
school ,
Quick R
Books: R in a nutshell ,
Art
of R programming,
Library
E-Books ,
Introductory
Statistics with R