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44 KiB
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101 lines
44 KiB
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<meta charset="utf-8">
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<meta name="generator" content="litedown 0.4">
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<title>Not An Introduction to knitr</title>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@xiee/utils@1.13.44/css/prism-xcode.min.css">
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@xiee/utils@1.13.44/css/default.min.css">
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</head>
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<body>
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<div class="frontmatter">
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<div class="title"><h1>Not An Introduction to knitr</h1></div>
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<div class="author"><h2>Yihui Xie</h2></div>
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<div class="date"><h3>2024-11-06</h3></div>
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</div>
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<div class="body">
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<p>The <strong>knitr</strong> package is an alternative tool to Sweave based on a different
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design with more features. This document is not an introduction, but only serves
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as a placeholder to guide you to the real manuals, which are available on the
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package website <a href="https://yihui.org/knitr/">https://yihui.org/knitr/</a> (e.g. the <a href="https://yihui.org/knitr/demo/manual/">main
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manual</a> and the <a href="https://yihui.org/knitr/demo/graphics/">graphics
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manual</a> ), and remember to read the help
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pages of functions in this package. There is a book “Dynamic Docuemnts with R
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and knitr” for this package, too.</p>
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<p>Anyway, here is a code chunk that shows you can compile vignettes with <strong>knitr</strong>
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as well using R 3.0.x, which supports non-Sweave vignettes:</p>
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<pre><code class="language-r">options(digits = 4)
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rnorm(20)
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</code></pre>
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<pre><code>#> [1] -0.53125 -1.10327 0.77924 -1.64279 2.12976 0.14292 -0.61442 -0.83602
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#> [9] 0.55669 -3.08241 -1.60739 -0.51008 1.40616 0.10845 2.56358 -0.66988
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#> [17] -1.49418 -0.19985 -0.07476 -0.43768
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</code></pre>
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<pre><code class="language-r">fit = lm(dist ~ speed, data = cars)
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b = coef(fit)
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</code></pre>
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<table>
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<thead>
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<tr>
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<th></th>
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<th align="right">Estimate</th>
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<th align="right">Std. Error</th>
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<th align="right">t value</th>
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<th align="right">Pr(>|t|)</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>(Intercept)</td>
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<td align="right">-17.579</td>
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<td align="right">6.758</td>
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<td align="right">-2.601</td>
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<td align="right">0.012</td>
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</tr>
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<tr>
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<td>speed</td>
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<td align="right">3.932</td>
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<td align="right">0.416</td>
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<td align="right">9.464</td>
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<td align="right">0.000</td>
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</tr>
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</tbody>
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</table>
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<p>The fitted regression equation is \(Y=-17.6+3.93x\).</p>
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<pre><code class="language-r">par(mar=c(4, 4, 1, .1))
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plot(cars, pch = 20)
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abline(fit, col = 'red')
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</code></pre>
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<div id="fig:graphics" class="figure">
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<p><img src="data:image/png;base64,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<div class="fig-caption">
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<p><span class="ref-number-fig">1</span>
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A scatterplot with a regression line.</p>
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</div>
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</div>
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<h2 id="sec:references">References</h2>
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<p>Xie Y (2024).
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<em>knitr: A General-Purpose Package for Dynamic Report Generation in R</em>.
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R package version 1.49, <a href="https://yihui.org/knitr/">https://yihui.org/knitr/</a>.
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</p>
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<p>Xie Y (2015).
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<em>Dynamic Documents with R and knitr</em>, 2nd edition.
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Chapman and Hall/CRC, Boca Raton, Florida.
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ISBN 978-1498716963, <a href="https://yihui.org/knitr/">https://yihui.org/knitr/</a>.
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</p>
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<p>Xie Y (2014).
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“knitr: A Comprehensive Tool for Reproducible Research in R.”
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In Stodden V, Leisch F, Peng RD (eds.), <em>Implementing Reproducible Computational Research</em>.
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Chapman and Hall/CRC.
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ISBN 978-1466561595.
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</p>
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</div>
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