Theknitr package is an alternative tool to Sweave based on a differentdesign with more features. This document is not an introduction, but only servesas a placeholder to guide you to the real manuals, which are available on thepackage websitehttps://yihui.org/knitr/ (e.g. themainmanual and thegraphicsmanual ), and remember to read the helppages of functions in this package. There is a book “Dynamic Docuemnts with Rand knitr” for this package, too.
Below are code chunk examples:
options(digits = 4)rnorm(20)#> [1] 1.58750 -0.16827 -1.83852 1.03203 -0.57857 0.80646 -1.59546 0.24443#> [9] -0.28545 0.96251 0.55820 -0.99688 0.02842 0.12531 0.85322 -1.23343#> [17] 0.70548 -0.89049 1.07269 -1.98522fit = lm(dist ~ speed, data = cars)b = coef(fit)| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | -17.579 | 6.758 | -2.601 | 0.012 |
| speed | 3.932 | 0.416 | 9.464 | 0.000 |
The fitted regression equation is \(Y=-17.6+3.93x\).
par(mar=c(4, 4, 1, .1))plot(cars, pch = 20)abline(fit, col = 'red')1A scatterplot with a regression line.
References
Xie Y (2025).knitr: A General-Purpose Package for Dynamic Report Generation in R.R package version 1.50,https://yihui.org/knitr/.
Xie Y (2015).Dynamic Documents with R and knitr, 2nd edition.Chapman and Hall/CRC, Boca Raton, Florida.ISBN 978-1498716963,https://yihui.org/knitr/.
Xie Y (2014).“knitr: A Comprehensive Tool for Reproducible Research in R.”In Stodden V, Leisch F, Peng RD (eds.),Implementing Reproducible Computational Research.Chapman and Hall/CRC.ISBN 978-1466561595.