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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# QregBB
<!-- badges: start -->
<!-- badges: end -->
The R package QregBB accompanies the paper:
Gregory, K.B., Lahiri, S.N., Nordman, D.J. (2018). A smooth block bootstrap for quantile regression with time series. *Annals of Statistics* 46(3), 1138-1166
Find the paper at https://projecteuclid.org/euclid.aos/1525313078.
## Installation
You can install the development version of QregBB from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("gregorkb/QregBB")
```
## Examples
The main function in the package is `QregBB`, which performs the MBB, SMBB, ETBB, and SETBB bootstrap procedures (all at once) for estimating the sampling distributions of quantile regression estimators with time series data.
```{r QregBB_example}
library(QregBB)
n <- 50
X1 <- arima.sim(model=list(ar=c(.7,.1)),n)
X2 <- arima.sim(model=list(ar=c(.2,.1)),n)
e <- arima.sim(model=list(ar=c(.7,.1)),n)
Y <- X1 + e
X <- cbind(rep(1,n),X1,X2)
QregBB.out <- QregBB(Y,X,tau=.5,l=4,B=500,h=NULL,alpha=0.05)
QregBB.out
```
The function `getNPPIblksizesQR` implements the block size selection method described in Gregory et al. (2018) for MBB, SMBB, ETBB, and SETBB.
```{r getNPPIblksizesQR_example}
blksize.out <- getNPPIblksizesQR(Y,X,tau=.5)
blksize.out
```
<!--
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