The knitr package is an alternative tool to Sweave based on a different design with more features. This document is not an introduction, but only serves as a placeholder to guide you to the real manuals, which are available on the package website https://yihui.org/knitr/ (e.g. the main manual and the graphics manual ), and remember to read the help pages of functions in this package. There is a book “Dynamic Docuemnts with R and knitr” for this package, too.
Anyway, here is a code chunk that shows you can compile vignettes with knitr as well using R 3.0.x, which supports non-Sweave vignettes:
options(digits = 4)
rnorm(20)
## [1] 0.8206 0.1908 0.7016 -0.5137 0.1895 -0.8288 -0.3375 -0.6747 -1.1224
## [10] 0.3149 0.4923 -0.7761 -1.7480 0.6905 0.5005 0.8479 1.4126 -0.7107
## [19] 0.1640 2.1599
fit = lm(dist ~ speed, data = cars)
b = coef(fit)
| Estimate | Std. Error | t value | Pr(>|t|) | |
|---|---|---|---|---|
| (Intercept) | -17.579 | 6.7584 | -2.601 | 0.0123 |
| speed | 3.932 | 0.4155 | 9.464 | 0.0000 |
The fitted regression equation is \(Y=-17.5791+3.9324x\).
par(mar=c(4, 4, 1, .1))
plot(cars, pch = 20)
abline(fit, col = 'red')
References
Xie Y (2024). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.47, 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.