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-<title>inverse.predict. chemCal 0.1-37</title>
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-
- <h1>Predict x from y for a linear calibration</h1>
-
-<div class="row">
- <div class="span8">
- <h2>Usage</h2>
- <pre><span class="functioncall"><a href='inverse.predict.html'>inverse.predict</a></span><span class="keyword">(</span><span class="symbol">object</span><span class="keyword">,</span> <span class="symbol">newdata</span><span class="keyword">,</span> <span class="symbol">...</span><span class="keyword">,</span>
- <span class="symbol">ws</span><span class="keyword">,</span> <span class="argument">alpha</span><span class="argument">=</span><span class="number">0.05</span><span class="keyword">,</span> <span class="argument">var.s</span>&nbsp;<span class="argument">=</span>&nbsp;<span class="string">"auto"</span><span class="keyword">)</span></pre>
-
- <h2>Arguments</h2>
- <dl>
- <dt>object</dt>
- <dd>
- A univariate model object of class <code><a href='http://www.rdocumentation.org/packages/stats/topics/lm'>lm</a></code> or
- <code><a href='http://www.rdocumentation.org/packages/MASS/topics/rlm'>rlm</a></code>
- with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>.
- </dd>
- <dt>newdata</dt>
- <dd>
- A vector of observed y values for one sample.
- </dd>
- <dt>...</dt>
- <dd>
- Placeholder for further arguments that might be needed by
- future implementations.
- </dd>
- <dt>ws</dt>
- <dd>
- The weight attributed to the sample. This argument is obligatory
- if <code>object</code> has weights.
- </dd>
- <dt>alpha</dt>
- <dd>
- The error tolerance level for the confidence interval to be reported.
- </dd>
- <dt>var.s</dt>
- <dd>
- The estimated variance of the sample measurements. The default is to take
- the residual standard error from the calibration and to adjust it
- using <code>ws</code>, if applicable. This means that <code>var.s</code>
- overrides <code>ws</code>.
- </dd>
- </dl>
-
- <div class="Value">
- <h2>Value</h2>
-
- <p><dl>
- A list containing the predicted x value, its standard error and a
- confidence interval.
-</dl></p>
-
- </div>
-
- <div class="Description">
- <h2>Description</h2>
-
- <p>This function predicts x values using a univariate linear model that has been
- generated for the purpose of calibrating a measurement method. Prediction
- intervals are given at the specified confidence level.
- The calculation method was taken from Massart et al. (1997). In particular,
- Equations 8.26 and 8.28 were combined in order to yield a general treatment
- of inverse prediction for univariate linear models, taking into account
- weights that have been used to create the linear model, and at the same
- time providing the possibility to specify a precision in sample measurements
- differing from the precision in standard samples used for the calibration.
- This is elaborated in the package vignette.</p>
-
- </div>
-
- <div class="Note">
- <h2>Note</h2>
-
- <p>The function was validated with examples 7 and 8 from Massart et al. (1997).</p>
-
- </div>
-
- <div class="References">
- <h2>References</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,
- p. 200</p>
-
- </div>
-
- <h2 id="examples">Examples</h2>
- <pre class="examples"><div class='input'><span class="comment"># This is example 7 from Chapter 8 in Massart et al. (1997)</span>
-<span class="functioncall"><a href='http://www.rdocumentation.org/packages/utils/topics/data'>data</a></span><span class="keyword">(</span><span class="symbol">massart97ex1</span><span class="keyword">)</span>
-<span class="symbol">m</span> <span class="assignement">&lt;-</span> <span class="functioncall"><a href='http://www.rdocumentation.org/packages/stats/topics/lm'>lm</a></span><span class="keyword">(</span><span class="symbol">y</span> <span class="keyword">~</span> <span class="symbol">x</span><span class="keyword">,</span> <span class="argument">data</span> <span class="argument">=</span> <span class="symbol">massart97ex1</span><span class="keyword">)</span>
-<span class="functioncall"><a href='inverse.predict.html'>inverse.predict</a></span><span class="keyword">(</span><span class="symbol">m</span><span class="keyword">,</span> <span class="number">15</span><span class="keyword">)</span> <span class="comment"># 6.1 +- 4.9</span></div>
-<div class='output'>$Prediction
-[1] 6.09381
-
-$`Standard Error`
-[1] 1.767278
-
-$Confidence
-[1] 4.906751
-
-$`Confidence Limits`
-[1] 1.187059 11.000561
-
-</div>
-<div class='input'><span class="functioncall"><a href='inverse.predict.html'>inverse.predict</a></span><span class="keyword">(</span><span class="symbol">m</span><span class="keyword">,</span> <span class="number">90</span><span class="keyword">)</span> <span class="comment"># 43.9 +- 4.9</span></div>
-<div class='output'>$Prediction
-[1] 43.93983
-
-$`Standard Error`
-[1] 1.767747
-
-$Confidence
-[1] 4.908053
-
-$`Confidence Limits`
-[1] 39.03178 48.84788
-
-</div>
-<div class='input'><span class="functioncall"><a href='inverse.predict.html'>inverse.predict</a></span><span class="keyword">(</span><span class="symbol">m</span><span class="keyword">,</span> <span class="functioncall"><a href='http://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span><span class="keyword">(</span><span class="number">90</span><span class="keyword">,</span><span class="number">5</span><span class="keyword">)</span><span class="keyword">)</span> <span class="comment"># 43.9 +- 3.2</span></div>
-<div class='output'>$Prediction
-[1] 43.93983
-
-$`Standard Error`
-[1] 1.141204
-
-$Confidence
-[1] 3.168489
-
-$`Confidence Limits`
-[1] 40.77134 47.10832
-
-</div></pre>
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