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| author | Johannes Ranke <jranke@uni-bremen.de> | 2022-03-23 10:32:36 +0100 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2022-03-31 18:35:09 +0200 |
| commit | f4fcef8228ebd5a1a73bc6edc47b5efa259c2e20 (patch) | |
| tree | f9e0489c8941257b5055783a443f4859212ad4f1 /docs/reference/massart97ex3.html | |
| parent | 4c2b22d75cc5102ddc595ea479c46bfdb46c1016 (diff) | |
Use 'investr' conditionally in tests, updates
Most prominently, a README was added, giving a nice
overview for the people visiting the github page, the
package page on CRAN, or the online docs at pkgdown.jrwb.de.
The maintainer e-mail address was also updated.
Diffstat (limited to 'docs/reference/massart97ex3.html')
| -rw-r--r-- | docs/reference/massart97ex3.html | 276 |
1 files changed, 107 insertions, 169 deletions
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(1997), example 3 — massart97ex3 • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Calibration data from Massart et al. (1997), example 3 — massart97ex3"><meta property="og:description" content="Sample dataset from p. 188 to test the package."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> -<![endif]--> - - - - </head> +<![endif]--></head><body data-spy="scroll" data-target="#toc"> + - <body data-spy="scroll" data-target="#toc"> <div class="container template-reference-topic"> - <header> - <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <header><div class="navbar navbar-default navbar-fixed-top" role="navigation"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> @@ -72,19 +17,12 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">chemCal</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.2</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.2.3</span> </span> </div> <div id="navbar" class="navbar-collapse collapse"> - <ul class="nav navbar-nav"> - <li> - <a href="../index.html"> - <span class="fas fa-home fa-lg"></span> - - </a> -</li> -<li> + <ul class="nav navbar-nav"><li> <a href="../articles/chemCal.html">Get started</a> </li> <li> @@ -93,25 +31,19 @@ <li> <a href="../news/index.html">Changelog</a> </li> - </ul> - <ul class="nav navbar-nav navbar-right"> - <li> - <a href="https://github.com/jranke/chemCal/"> + </ul><ul class="nav navbar-nav navbar-right"><li> + <a href="https://github.com/jranke/chemCal/" class="external-link"> <span class="fab fa-github fa-lg"></span> </a> </li> - </ul> - - </div><!--/.nav-collapse --> + </ul></div><!--/.nav-collapse --> </div><!--/.container --> </div><!--/.navbar --> - </header> - -<div class="row"> + </header><div class="row"> <div class="col-md-9 contents"> <div class="page-header"> <h1>Calibration data from Massart et al. (1997), example 3</h1> @@ -123,117 +55,123 @@ <p>Sample dataset from p. 188 to test the package.</p> </div> - <pre class="usage"><span class='va'>massart97ex3</span></pre> - - - <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> + <div id="ref-usage"> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">massart97ex3</span></code></pre></div> + </div> + <div id="format"> + <h2>Format</h2> <p>A dataframe containing 6 levels of x values with 5 observations of y for each level.</p> - <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2> - + </div> + <div id="source"> + <h2>Source</h2> <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A, Chapter 8.</p> + </div> - <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> - <pre class="examples"><div class='input'><span class='co'># For reproducing the results for replicate standard measurements in example 8,</span> -<span class='co'># we need to do the calibration on the means when using chemCal > 0.2</span> -<span class='va'>weights</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/with.html'>with</a></span><span class='op'>(</span><span class='va'>massart97ex3</span>, <span class='op'>{</span> - <span class='va'>yx</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/split.html'>split</a></span><span class='op'>(</span><span class='va'>y</span>, <span class='va'>x</span><span class='op'>)</span> - <span class='va'>ybar</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>sapply</a></span><span class='op'>(</span><span class='va'>yx</span>, <span class='va'>mean</span><span class='op'>)</span> - <span class='va'>s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/Round.html'>round</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>sapply</a></span><span class='op'>(</span><span class='va'>yx</span>, <span class='va'>sd</span><span class='op'>)</span>, digits <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span> - <span class='va'>w</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/Round.html'>round</a></span><span class='op'>(</span><span class='fl'>1</span> <span class='op'>/</span> <span class='op'>(</span><span class='va'>s</span><span class='op'>^</span><span class='fl'>2</span><span class='op'>)</span>, digits <span class='op'>=</span> <span class='fl'>3</span><span class='op'>)</span> -<span class='op'>}</span><span class='op'>)</span> - -<span class='va'>massart97ex3.means</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/aggregate.html'>aggregate</a></span><span class='op'>(</span><span class='va'>y</span> <span class='op'>~</span> <span class='va'>x</span>, <span class='va'>massart97ex3</span>, <span class='va'>mean</span><span class='op'>)</span> - -<span class='va'>m3.means</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span><span class='op'>(</span><span class='va'>y</span> <span class='op'>~</span> <span class='va'>x</span>, w <span class='op'>=</span> <span class='va'>weights</span>, data <span class='op'>=</span> <span class='va'>massart97ex3.means</span><span class='op'>)</span> - -<span class='co'># The following concords with the book p. 200</span> -<span class='fu'><a href='inverse.predict.html'>inverse.predict</a></span><span class='op'>(</span><span class='va'>m3.means</span>, <span class='fl'>15</span>, ws <span class='op'>=</span> <span class='fl'>1.67</span><span class='op'>)</span> <span class='co'># 5.9 +- 2.5</span> -</div><div class='output co'>#> $Prediction -#> [1] 5.865367 -#> -#> $`Standard Error` -#> [1] 0.8926109 -#> -#> $Confidence -#> [1] 2.478285 -#> -#> $`Confidence Limits` -#> [1] 3.387082 8.343652 -#> </div><div class='input'><span class='fu'><a href='inverse.predict.html'>inverse.predict</a></span><span class='op'>(</span><span class='va'>m3.means</span>, <span class='fl'>90</span>, ws <span class='op'>=</span> <span class='fl'>0.145</span><span class='op'>)</span> <span class='co'># 44.1 +- 7.9</span> -</div><div class='output co'>#> $Prediction -#> [1] 44.06025 -#> -#> $`Standard Error` -#> [1] 2.829162 -#> -#> $Confidence -#> [1] 7.855012 -#> -#> $`Confidence Limits` -#> [1] 36.20523 51.91526 -#> </div><div class='input'> -<span class='co'># The LOD is only calculated for models from unweighted regression</span> -<span class='co'># with this version of chemCal</span> -<span class='va'>m0</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span><span class='op'>(</span><span class='va'>y</span> <span class='op'>~</span> <span class='va'>x</span>, data <span class='op'>=</span> <span class='va'>massart97ex3</span><span class='op'>)</span> -<span class='fu'><a href='lod.html'>lod</a></span><span class='op'>(</span><span class='va'>m0</span><span class='op'>)</span> -</div><div class='output co'>#> $x -#> [1] 5.407085 -#> -#> $y -#> [1] 13.63911 -#> </div><div class='input'> -<span class='co'># Limit of quantification from unweighted regression</span> -<span class='fu'><a href='loq.html'>loq</a></span><span class='op'>(</span><span class='va'>m0</span><span class='op'>)</span> -</div><div class='output co'>#> $x -#> [1] 9.627349 -#> -#> $y -#> [1] 22.00246 -#> </div><div class='input'> -<span class='co'># For calculating the limit of quantification from a model from weighted</span> -<span class='co'># regression, we need to supply weights, internally used for inverse.predict</span> -<span class='co'># If we are not using a variance function, we can use the weight from</span> -<span class='co'># the above example as a first approximation (x = 15 is close to our</span> -<span class='co'># loq approx 14 from above).</span> -<span class='fu'><a href='loq.html'>loq</a></span><span class='op'>(</span><span class='va'>m3.means</span>, w.loq <span class='op'>=</span> <span class='fl'>1.67</span><span class='op'>)</span> -</div><div class='output co'>#> $x -#> [1] 7.346195 -#> -#> $y -#> [1] 17.90777 -#> </div><div class='input'><span class='co'># The weight for the loq should therefore be derived at x = 7.3 instead</span> -<span class='co'># of 15, but the graphical procedure of Massart (p. 201) to derive the </span> -<span class='co'># variances on which the weights are based is quite inaccurate anyway. </span> -</div></pre> + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># For reproducing the results for replicate standard measurements in example 8,</span></span> +<span class="r-in"><span class="co"># we need to do the calibration on the means when using chemCal > 0.2</span></span> +<span class="r-in"><span class="va">weights</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html" class="external-link">with</a></span><span class="op">(</span><span class="va">massart97ex3</span>, <span class="op">{</span></span> +<span class="r-in"> <span class="va">yx</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/split.html" class="external-link">split</a></span><span class="op">(</span><span class="va">y</span>, <span class="va">x</span><span class="op">)</span></span> +<span class="r-in"> <span class="va">ybar</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">yx</span>, <span class="va">mean</span><span class="op">)</span></span> +<span class="r-in"> <span class="va">s</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">round</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">yx</span>, <span class="va">sd</span><span class="op">)</span>, digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span> +<span class="r-in"> <span class="va">w</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">round</a></span><span class="op">(</span><span class="fl">1</span> <span class="op">/</span> <span class="op">(</span><span class="va">s</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>, digits <span class="op">=</span> <span class="fl">3</span><span class="op">)</span></span> +<span class="r-in"><span class="op">}</span><span class="op">)</span></span> +<span class="r-in"></span> +<span class="r-in"><span class="va">massart97ex3.means</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/aggregate.html" class="external-link">aggregate</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, <span class="va">massart97ex3</span>, <span class="va">mean</span><span class="op">)</span></span> +<span class="r-in"></span> +<span class="r-in"><span class="va">m3.means</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, w <span class="op">=</span> <span class="va">weights</span>, data <span class="op">=</span> <span class="va">massart97ex3.means</span><span class="op">)</span></span> +<span class="r-in"></span> +<span class="r-in"><span class="co"># The following concords with the book p. 200</span></span> +<span class="r-in"><span class="fu"><a href="inverse.predict.html">inverse.predict</a></span><span class="op">(</span><span class="va">m3.means</span>, <span class="fl">15</span>, ws <span class="op">=</span> <span class="fl">1.67</span><span class="op">)</span> <span class="co"># 5.9 +- 2.5</span></span> +<span class="r-out co"><span class="r-pr">#></span> $Prediction</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 5.865367</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $`Standard Error`</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 0.8926109</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $Confidence</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 2.478285</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $`Confidence Limits`</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 3.387082 8.343652</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span class="fu"><a href="inverse.predict.html">inverse.predict</a></span><span class="op">(</span><span class="va">m3.means</span>, <span class="fl">90</span>, ws <span class="op">=</span> <span class="fl">0.145</span><span class="op">)</span> <span class="co"># 44.1 +- 7.9</span></span> +<span class="r-out co"><span class="r-pr">#></span> $Prediction</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 44.06025</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $`Standard Error`</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 2.829162</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $Confidence</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 7.855012</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $`Confidence Limits`</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 36.20523 51.91526</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"></span> +<span class="r-in"><span class="co"># The LOD is only calculated for models from unweighted regression</span></span> +<span class="r-in"><span class="co"># with this version of chemCal</span></span> +<span class="r-in"><span class="va">m0</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex3</span><span class="op">)</span> </span> +<span class="r-in"><span class="fu"><a href="lod.html">lod</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></span> +<span class="r-out co"><span class="r-pr">#></span> $x</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 5.407085</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $y</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 13.63911</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"></span> +<span class="r-in"><span class="co"># Limit of quantification from unweighted regression</span></span> +<span class="r-in"><span class="fu"><a href="loq.html">loq</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></span> +<span class="r-out co"><span class="r-pr">#></span> $x</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 9.627349</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $y</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 22.00246</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"></span> +<span class="r-in"><span class="co"># For calculating the limit of quantification from a model from weighted</span></span> +<span class="r-in"><span class="co"># regression, we need to supply weights, internally used for inverse.predict</span></span> +<span class="r-in"><span class="co"># If we are not using a variance function, we can use the weight from</span></span> +<span class="r-in"><span class="co"># the above example as a first approximation (x = 15 is close to our</span></span> +<span class="r-in"><span class="co"># loq approx 14 from above).</span></span> +<span class="r-in"><span class="fu"><a href="loq.html">loq</a></span><span class="op">(</span><span class="va">m3.means</span>, w.loq <span class="op">=</span> <span class="fl">1.67</span><span class="op">)</span></span> +<span class="r-out co"><span class="r-pr">#></span> $x</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 7.346195</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> $y</span> +<span class="r-out co"><span class="r-pr">#></span> [1] 17.90777</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span class="co"># The weight for the loq should therefore be derived at x = 7.3 instead</span></span> +<span class="r-in"><span class="co"># of 15, but the graphical procedure of Massart (p. 201) to derive the </span></span> +<span class="r-in"><span class="co"># variances on which the weights are based is quite inaccurate anyway. </span></span> +</code></pre></div> + </div> </div> <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> - <nav id="toc" data-toggle="toc" class="sticky-top"> - <h2 data-toc-skip>Contents</h2> - </nav> - </div> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> </div> - <footer> - <div class="copyright"> - <p>Developed by Johannes Ranke.</p> + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> </div> <div class="pkgdown"> - <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p> </div> - </footer> - </div> + </footer></div> - </body> -</html> + + </body></html> |