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diff --git a/inst/web/inverse.predict.html b/inst/web/inverse.predict.html new file mode 100644 index 0000000..855ee6a --- /dev/null +++ b/inst/web/inverse.predict.html @@ -0,0 +1,202 @@ +<!DOCTYPE html> +<html lang="en"> + <head> + <meta charset="utf-8"> +<title>inverse.predict. chemCal 0.1-35.900</title> +<meta name="viewport" content="width=device-width, initial-scale=1.0"> +<meta name="author" content=""> + +<link href="css/bootstrap.css" rel="stylesheet"> +<link href="css/bootstrap-responsive.css" rel="stylesheet"> +<link href="css/highlight.css" rel="stylesheet"> +<link href="css/staticdocs.css" rel="stylesheet"> + +<!--[if lt IE 9]> + <script src="http://html5shim.googlecode.com/svn/trunk/html5.js"></script> +<![endif]--> + +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + tex2jax: { + inlineMath: [ ['$','$'], ["\\(","\\)"] ], + processEscapes: true + } + }); +</script> +<script type="text/javascript" + src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"> +</script> + </head> + + <body> + <div class="navbar"> + <div class="navbar-inner"> + <div class="container"> + <a class="brand" href="#">chemCal 0.1-35.900</a> + <div class="nav"> + <ul class="nav"> + <li><a href="index.html"><i class="icon-home icon-white"></i> Index</a></li> + </ul> + </div> + </div> + </div> +</div> + + <div class="container"> + <header> + + </header> + + <h1>Predict x from y for a linear calibration</h1> + +<div class="row"> + <div class="span8"> + <h2>Usage</h2> + <pre><div>inverse.predict(object, newdata, ..., ws, alpha=0.05, var.s = "auto")</div></pre> + + <h2>Arguments</h2> + <dl> + <dt>object</dt> + <dd> + A univariate model object of class <code><a href='http://www.inside-r.org/r-doc/stats/lm'>lm</a></code> or + <code><a href='http://www.inside-r.org/r-doc/MASS/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'># This is example 7 from Chapter 8 in Massart et al. (1997) +data(massart97ex1) +m <- lm(y ~ x, data = massart97ex1) +inverse.predict(m, 15) # 6.1 +- 4.9 +</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'>inverse.predict(m, 90) # 43.9 +- 4.9 +</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'>inverse.predict(m, rep(90,5)) # 43.9 +- 3.2 +</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> + </div> + <div class="span4"> + <!-- <ul> + <li>inverse.predict</li><li>inverse.predict.lm</li><li>inverse.predict.rlm</li><li>inverse.predict.default</li> + </ul> + <ul> + <li>manip</li> + </ul> --> + + + </div> +</div> + + <footer> + <p class="pull-right"><a href="#">Back to top</a></p> +<p>Built by <a href="https://github.com/hadley/staticdocs">staticdocs</a>. 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