1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
|
<!DOCTYPE html>
<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Calibration data from Massart et al. (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><body data-spy="scroll" data-target="#toc">
<div class="container template-reference-topic">
<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">
<span class="sr-only">Toggle navigation</span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</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="">0.2.3</span>
</span>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav"><li>
<a href="../articles/chemCal.html">Get started</a>
</li>
<li>
<a href="../reference/index.html">Reference</a>
</li>
<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/" class="external-link">
<span class="fab fa-github fa-lg"></span>
</a>
</li>
</ul></div><!--/.nav-collapse -->
</div><!--/.container -->
</div><!--/.navbar -->
</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>
<div class="hidden name"><code>massart97ex3.Rd</code></div>
</div>
<div class="ref-description">
<p>Sample dataset from p. 188 to test the package.</p>
</div>
<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>
</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>
<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>
</div>
<footer><div class="copyright">
<p></p><p>Developed by Johannes Ranke.</p>
</div>
<div class="pkgdown">
<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>
</body></html>
|
