# Not An Introduction to knitr

## Yihui Xie

### 2025-12-19

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.

Below are code chunk examples:

    options(digits = 4)
    rnorm(20)

    #>  [1]  0.24673 -0.68330 -0.72681  0.08647  1.19383  1.31775 -0.25231 -0.61987
    #>  [9] -0.10383 -1.26826  0.31178  0.28086  0.09347 -0.61989 -0.79728 -1.33204
    #> [17]  0.33454 -0.11146 -0.94157 -0.30615

    fit = 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')

1 A scatterplot with a regression line.

## References

Xie Y (2025). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.51, 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.