README.md

In yixinsun1216/uggs: Bias Corrected and Accelerated Bootstrap Confidence Limits

uggs

A package that builds on the bcaboot package to compute bias corrected and accelerated bootstrap confidence limits . By implementing parallel computing using the furrr package, we are able to make substantial speed improvements.

For further information the bca bootstrapping method, refer to Computer Age Satistical Inference found here Or the manual for bcaboot

Installation

To install, use devtools::install_github("yixinsun1216/uggs")

Example

``` library(lfe) library(uggs)

## create covariates x1 <- rnorm(1000) x2 <- rnorm(length(x1))

## fixed effects fe <- factor(sample(20, length(x1), replace=TRUE))

## effects for fe fe_effs <- rnorm(nlevels(fe))

## creating left hand side y u <- rnorm(length(x1)) y <- 2 * x1 + x2 + fe_effs[fe] + u

# create dataframe to pass into uggs df_test <- as.data.frame(cbind(y, x1, x2, fe))

# function that returns parameter of interest, x1 est_test <- function(df){ m <- felm(y ~ x1 + x2 | fe, df) as.numeric(coef(m)["x1"]) }

x1_boot <- uggs(df_test, 1000, est_test, jcount = 40, jreps = 5)

x1_boot $limits bca std pct jacksd 0.025 1.977667 1.975631 0.029 0.004010308 0.05 1.987274 1.985915 0.054 0.001749787 0.1 1.996758 1.99777 0.102 0.004436592 0.5 2.038755 2.039592 0.486 0.001477231 0.9 2.08201 2.081414 0.902 0.002506374 0.95 2.096626 2.09327 0.954 0.004449781 0.975 2.106012 2.103553 0.979 0.001599195

$stats theta sdboot z0 a sdjack est 2.039592 0.0326336866 -0.01754730 0.02673691 0.0315359 jsd 0.000000 0.0007583239 0.03020335 0.00000000 0.0000000

$B.mean [1] 1000.000000 2.039816

$ustats ustat sdu 2.0393682 0.1367483 ```

yixinsun1216/uggs documentation built on May 28, 2019, 12:05 p.m.