The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
The goal of lfe is to speed up the estimation of linear models with large fixed effects. It includes support for instrumental variables, conditional F statistics for weak instruments, robust and multi-way clustered standard errors, as well as limited mobility bias correction. See Gaure (2013) doi:10.1016/j.csda.2013.03.024 and Gaure 2014 doi:10.1002/sta4.68.
You can install the released version of lfe from CRAN with:
You can install the development version of lfe like so:
This is a basic example which shows you the speed improvement over base R for fixed effects estimation.
library(lfe) # fixed effects estimation
library(tradepolicy) # intl trade data
library(dplyr) # data cleaning/transforming
training_data <- agtpa_applications %>%
mutate(
log_trade = log(trade),
log_dist = log(dist),
exp_year = paste(exporter, year, sep = "_"),
imp_year = paste(importer, year, sep = "_")
) %>%
filter(trade > 0, exporter != importer, year %in% seq(1986, 2006, 4)) %>%
select(year, log_trade, log_dist, cntg, lang, clny, rta, exp_year, imp_year)
# note the difference with the | operator to indicate the FEs
# this is just an example, here I am not estimating a PPML model or anything
# in the state of the art
fml1 <- 0 + log_trade ~
log_dist + cntg + lang + clny + rta + exp_year + imp_year # base
fml2 <- log_trade ~
log_dist + cntg + lang + clny + rta | exp_year + imp_year # lfe
lm(fml1, data = training_data)
felm(fml2, data = training_data)For a complete test with devtools::check(), you need to run sudo apt-get install devtools or similar before. The package is written in C, in the future I shall try to rewrite it in C++ to ease long term maintenance.
The package also needs additional testing. At the present time,the tests it cover around 30% of the written lines.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.