Sparse matrices in RcppArmadillo can be a very useful resource to work with, especially when you are dealing with social networks. Here I provide a couple of examples in which we can take advantage of their structure by using iterators.
I’m a Chilean working and getting a Ph.D. at USC on Statistical Computing at the Department of Preventive Medicine with with Prof. Thomas W. Valente and Prof. Paul Marjoram. I hold a MA in Economics and Public Policy from Universidad Adolfo Ibáñez (Chile) and a M.Sc. in Economics from the California Institute of Technology (USA). Currently, I’m interested in social networks, developing (and implementing) new statistical methods for data analysis (and inference), statistical computing, and computational social sciences in general.
Some quick links
netdiffuseR, twitterreport, rgexf, parallel, ABCoptim, Center for Applied Network Analysis
Ph.D. in Biostatistics, 2017-
University of Southern California
M.Sc. in Economics, 2016
California Institute of Technology
M.A. in Economics and Public Policy, 2010
Universidad Adolfo Ibáñez, Chile
Aug 7, 2018, USC’s High Performance Computing Center Workshops
Mar 29, 2018, The “Happy Scientist” Seminar Series
Jul 27, 2017, Stata Conference, 2017
Mar 23, 2017, The “Happy Scientist” Seminar Series
Nov 17, 2016, USC’s Center for Applied Network Analysis (CANA)
Sep 19, 2016, USC’s Health Behavior Research, Students Seminars
Jun 16, 2016, The R User Conference 2016
Sparse matrices in RcppArmadillo can be a very useful resource to work with, especially when you are dealing with social networks. Here I provide a couple of examples in which we can take advantage of their structure by using iterators.
Finally, after a long wait, the R packages googlePublicData (more than 2 years since the last update!) and ABCoptim (roughly a year since the last update) have new versions on CRAN.
Parallel lets you run Stata faster, sometimes faster than MP itself. By organizing your job in several Stata instances, parallel allows you to work with out-of-the-box parallel computing.
The aphylo R package implements estimation and data imputation methods for Functional Annotations in Phylogenetic Trees.
Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks.