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diff --git a/docs/reference/loq.html b/docs/reference/loq.html index ad7fa86..2fb01a8 100644 --- a/docs/reference/loq.html +++ b/docs/reference/loq.html @@ -18,19 +18,34 @@ <!-- 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="Estimate a limit of quantification (LOQ) — loq" /> +<meta property="og:description" content="The limit of quantification is the x value, where the relative error + of the quantification given the calibration model reaches a prespecified + value 1/k. Thus, it is the solution of the equation + $$L = k c(L)$$ + where c(L) is half of the length of the confidence interval at the limit L + (DIN 32645, equivalent to ISO 11843). c(L) is internally estimated by + inverse.predict, and L is obtained by iteration." /> +<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> @@ -79,62 +94,63 @@ $$L = k c(L)$$ where c(L) is half of the length of the confidence interval at the limit L (DIN 32645, equivalent to ISO 11843). c(L) is internally estimated by - <code><a href='inverse.predict.html'>inverse.predict</a></code>, and L is obtained by iteration.</p> + <code>inverse.predict</code>, and L is obtained by iteration.</p> - <pre>loq(object, …, alpha = 0.05, k = 3, n = 1, w.loq = "auto", + <pre class="usage">loq(object, …, alpha = 0.05, k = 3, n = 1, w.loq = "auto", var.loq = "auto", tol = "default")</pre> <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2> - <dl class="dl-horizontal"> - <dt>object</dt> - <dd> - A univariate model object of class <code>lm</code> or + <table class="ref-arguments"> + <colgroup><col class="name" /><col class="desc" /></colgroup> + <tr> + <th>object</th> + <td><p>A univariate model object of class <code>lm</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>, optionally from a weighted regression. If weights are specified in the model, either <code>w.loq</code> or <code>var.loq</code> have to - be specified. - </dd> - <dt>alpha</dt> - <dd> - The error tolerance for the prediction of x values in the calculation. - </dd> - <dt>…</dt> - <dd> - Placeholder for further arguments that might be needed by - future implementations. - </dd> - <dt>k</dt> - <dd> - The inverse of the maximum relative error tolerated at the - desired LOQ. - </dd> - <dt>n</dt> - <dd> - The number of replicate measurements for which the LOQ should be - specified. - </dd> - <dt>w.loq</dt> - <dd> - The weight that should be attributed to the LOQ. Defaults + be specified.</p></td> + </tr> + <tr> + <th>alpha</th> + <td><p>The error tolerance for the prediction of x values in the calculation.</p></td> + </tr> + <tr> + <th>…</th> + <td><p>Placeholder for further arguments that might be needed by + future implementations.</p></td> + </tr> + <tr> + <th>k</th> + <td><p>The inverse of the maximum relative error tolerated at the + desired LOQ.</p></td> + </tr> + <tr> + <th>n</th> + <td><p>The number of replicate measurements for which the LOQ should be + specified.</p></td> + </tr> + <tr> + <th>w.loq</th> + <td><p>The weight that should be attributed to the LOQ. Defaults to one for unweighted regression, and to the mean of the weights - for weighted regression. See <code><a href='massart97ex3.html'>massart97ex3</a></code> for + for weighted regression. See <code>massart97ex3</code> for an example how to take advantage of knowledge about the - variance function. - </dd> - <dt>var.loq</dt> - <dd> - The approximate variance at the LOQ. The default value is - calculated from the model. - </dd> - <dt>tol</dt> - <dd> - The default tolerance for the LOQ on the x scale is the value of the + variance function.</p></td> + </tr> + <tr> + <th>var.loq</th> + <td><p>The approximate variance at the LOQ. The default value is + calculated from the model.</p></td> + </tr> + <tr> + <th>tol</th> + <td><p>The default tolerance for the LOQ on the x scale is the value of the smallest non-zero standard divided by 1000. Can be set to a - numeric value to override this. - </dd> - </dl> + numeric value to override this.</p></td> + </tr> + </table> <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> @@ -149,7 +165,7 @@ <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2> - <p>Examples for <code><a href='din32645.html'>din32645</a></code></p> + <p>Examples for <code>din32645</code></p> <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> @@ -195,7 +211,7 @@ </div> <div class="pkgdown"> - <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p> + <p>Site built with <a href="http://pkgdown.r-lib.org/">pkgdown</a>.</p> </div> </footer> |