Package: Zelig
Maintainer: James Honaker <zelig-zee@iq.harvard.edu>
License: GPL (>= 2)
Title: Everyone's Statistical Software
Author: Matt Owen <mowen@iq.harvard.edu>, Kosuke Imai
<kimai@Princeton.Edu>, Gary King <king@harvard.edu>, Olivia Lau
<olau@fas.harvard.edu>
Description: Zelig is an easy-to-use program that can estimate, and
help interpret the results of, an enormous range of statistical
models. It literally is ``everyone's statistical software'' because
Zelig's simple unified framework incorporates everyone else's (R)
code. We also hope it will become ``everyone's statistical
software'' for applications and teaching, and so have designed
Zelig so that anyone can easily use it or add their programs to it.
Zelig also comes with infrastructure that facilitates the use of
any existing method, such as by allowing multiply imputed data for
any model, and mimicking the program Clarify (for Stata) that takes
the raw output of existing statistical procedures and translates
them into quantities of direct interest.
Version: 4.2-1
URL: http://gking.harvard.edu/zelig
Date: 2013-09-12
Depends: R (>= 2.14), boot, MASS, methods, sandwich
Suggests: Amelia, mvtnorm, Formula, gee, survey, survival, systemfit,
MatchIt, MCMCpack, coda
Packaged: 2013-09-20 23:15:59 UTC; jhonaker
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-09-21 08:14:26

Author: Christine Choirat, James Honaker, Kosuke Imai, Gary King, Olivia Lau
Description: A framework that brings together an abundance of common
statistical models found across packages into a unified interface, and
provides a common architecture for estimation and interpretation, as well
as bridging functions to absorb increasingly more models into the
collective library.  Zelig allows each individual package, for each
statistical model, to be accessed by a common uniformly structured call and
set of arguments.  Moreover, Zelig automates all the surrounding building
blocks of a statistical work-flow --procedures and algorithms that may be
essential to one user's application but which the original package
developer did not use in their own research and might not themselves
support. These include bootstrapping, jackknifing, and re-weighting of data.
In particular, Zelig automatically generates predicted and simulated
quantities of interest (such as relative risk ratios, average treatment
effects, first differences and predicted and expected values) to interpret
Imports: sandwich, methods, MASS, survival, VGAM, jsonlite, AER, plyr,
dplyr (>= 0.3.0.2), quantreg, geepack, MCMCpack, Amelia,
Collate: 'utils.R' 'model-zelig.R' 'model-weibull.R' 'model-tobit.R'