fastStat: Faster for Statistic Work

When we do statistic work, we need to see the structure of the data. list.str() function will help you see the structure of the data quickly. list.plot() function can help you check every variable in your dataframe. table_one() function will make it easy to make a baseline table including difference tests. uv_linear(), uv_logit(), uv_cox(), uv_logrank() will give you a hand to do univariable regression analysis, while mv_linear(), mv_logit() and mv_cox() will carry out multivariable regression analysis.

Version: 1.3
Imports: set, reshape2, do, plyr, car, e1071, tseries, survival, ggplot2, ggrepel
Published: 2019-11-22
Author: Jing Zhang [aut, cre], Zhi Jin [aut]
Maintainer: Jing Zhang <zj391120 at 163.com>
BugReports: https://github.com/yikeshu0611/fastStat/issues
License: GPL-3
URL: https://github.com/yikeshu0611/fastStat
NeedsCompilation: no
CRAN checks: fastStat results

Downloads:

Reference manual: fastStat.pdf
Package source: fastStat_1.3.tar.gz
Windows binaries: r-devel: fastStat_1.3.zip, r-devel-gcc8: fastStat_1.3.zip, r-release: fastStat_1.3.zip, r-oldrel: fastStat_1.3.zip
OS X binaries: r-release: fastStat_1.3.tgz, r-oldrel: fastStat_1.3.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=fastStat to link to this page.