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diff --git a/inst/web/inverse.predict.html b/inst/web/inverse.predict.html deleted file mode 100644 index a513357..0000000 --- a/inst/web/inverse.predict.html +++ /dev/null @@ -1,202 +0,0 @@ -<!DOCTYPE html> -<html lang="en"> - <head> - <meta charset="utf-8"> -<title>inverse.predict. chemCal 0.1-37</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 0.1-37</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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