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diff --git a/docs/reference/massart97ex3.html b/docs/reference/massart97ex3.html index 2946139..d737fc5 100644 --- a/docs/reference/massart97ex3.html +++ b/docs/reference/massart97ex3.html @@ -18,19 +18,28 @@ <!-- Font Awesome icons --> <link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" integrity="sha384-T8Gy5hrqNKT+hzMclPo118YTQO6cYprQmhrYwIiQ/3axmI1hQomh7Ud2hPOy8SP1" crossorigin="anonymous"> +<!-- clipboard.js --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/1.7.1/clipboard.min.js" integrity="sha384-cV+rhyOuRHc9Ub/91rihWcGmMmCXDeksTtCihMupQHSsi8GIIRDG0ThDc3HGQFJ3" crossorigin="anonymous"></script> <!-- pkgdown --> <link href="../pkgdown.css" rel="stylesheet"> <script src="../jquery.sticky-kit.min.js"></script> <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." /> +<meta name="twitter:card" content="summary" /> <!-- mathjax --> -<script src='https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></script> +<script src='https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></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> <body> @@ -76,7 +85,7 @@ <p>Sample dataset from p. 188 to test the package.</p> - <pre><span class='fu'>data</span>(<span class='no'>massart97ex3</span>)</pre> + <pre class="usage"><span class='fu'>data</span>(<span class='no'>massart97ex3</span>)</pre> <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> @@ -100,9 +109,9 @@ <span class='no'>w</span> <span class='kw'><-</span> <span class='fu'>round</span>(<span class='fl'>1</span> / (<span class='no'>s</span>^<span class='fl'>2</span>), <span class='kw'>digits</span> <span class='kw'>=</span> <span class='fl'>3</span>) <span class='no'>weights</span> <span class='kw'><-</span> <span class='no'>w</span>[<span class='fu'>factor</span>(<span class='no'>x</span>)] <span class='no'>m</span> <span class='kw'><-</span> <span class='fu'>lm</span>(<span class='no'>y</span> ~ <span class='no'>x</span>, <span class='kw'>w</span> <span class='kw'>=</span> <span class='no'>weights</span>) -<span class='fu'><a href='calplot.html'>calplot</a></span>(<span class='no'>m</span>)</div><div class='output co'>#> <span class='warning'>Warning: Assuming constant prediction variance even though model fit is weighted</span></div><img src='massart97ex3-5.png' alt='' width='540' height='400' /><div class='input'> +<span class='fu'>calplot</span>(<span class='no'>m</span>)</div><div class='output co'>#> <span class='warning'>Warning: Assuming constant prediction variance even though model fit is weighted</span></div><div class='img'><img src='massart97ex3-1.png' alt='' width='700' height='432.632880098887' /></div><div class='input'> <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='no'>m</span>, <span class='fl'>15</span>, <span class='kw'>ws</span> <span class='kw'>=</span> <span class='fl'>1.67</span>) <span class='co'># 5.9 +- 2.5</span></div><div class='output co'>#> $Prediction +<span class='fu'>inverse.predict</span>(<span class='no'>m</span>, <span class='fl'>15</span>, <span class='kw'>ws</span> <span class='kw'>=</span> <span class='fl'>1.67</span>) <span class='co'># 5.9 +- 2.5</span></div><div class='output co'>#> $Prediction #> [1] 5.865367 #> #> $`Standard Error` @@ -113,7 +122,7 @@ #> #> $`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='no'>m</span>, <span class='fl'>90</span>, <span class='kw'>ws</span> <span class='kw'>=</span> <span class='fl'>0.145</span>) <span class='co'># 44.1 +- 7.9</span></div><div class='output co'>#> $Prediction +#> </div><div class='input'><span class='fu'>inverse.predict</span>(<span class='no'>m</span>, <span class='fl'>90</span>, <span class='kw'>ws</span> <span class='kw'>=</span> <span class='fl'>0.145</span>) <span class='co'># 44.1 +- 7.9</span></div><div class='output co'>#> $Prediction #> [1] 44.06025 #> #> $`Standard Error` @@ -128,7 +137,7 @@ <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='no'>m0</span> <span class='kw'><-</span> <span class='fu'>lm</span>(<span class='no'>y</span> ~ <span class='no'>x</span>) -<span class='fu'><a href='lod.html'>lod</a></span>(<span class='no'>m0</span>)</div><div class='output co'>#> $x +<span class='fu'>lod</span>(<span class='no'>m0</span>)</div><div class='output co'>#> $x #> [1] 5.407085 #> #> $y @@ -136,7 +145,7 @@ #> 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='no'>m0</span>)</div><div class='output co'>#> $x +<span class='fu'>loq</span>(<span class='no'>m0</span>)</div><div class='output co'>#> $x #> [1] 13.97764 #> #> $y @@ -148,15 +157,16 @@ <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='no'>m</span>, <span class='kw'>w.loq</span> <span class='kw'>=</span> <span class='fl'>1.67</span>)</div><div class='output co'>#> $x +<span class='fu'>loq</span>(<span class='no'>m</span>, <span class='kw'>w.loq</span> <span class='kw'>=</span> <span class='fl'>1.67</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><div class='input'># The weight for the loq should therefore be derived at x = 7.3 instead +# of 15, but the graphical procedure of Massart (p. 201) to derive the +# variances on which the weights are based is quite inaccurate anyway. +</div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="sidebar"> <h2>Contents</h2> @@ -178,7 +188,7 @@ </div> <div class="pkgdown"> - <p>Site built with <a 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