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SSlogis.html
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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html><head><title>R: Self-Starting Nls Logistic Model</title>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<link rel="stylesheet" type="text/css" href="R.css">
</head><body>
<table width="100%" summary="page for SSlogis"><tr><td>SSlogis</td><td align="right">R Documentation</td></tr></table>
<h2>Self-Starting Nls Logistic Model</h2>
<h3>Description</h3>
<p>This <code>selfStart</code> model evaluates the logistic
function and its gradient. It has an <code>initial</code> attribute that
creates initial estimates of the parameters <code>Asym</code>,
<code>xmid</code>, and <code>scal</code>.
</p>
<h3>Usage</h3>
<pre>
SSlogis(input, Asym, xmid, scal)
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>input</code></td>
<td>
<p>a numeric vector of values at which to evaluate the model.</p>
</td></tr>
<tr valign="top"><td><code>Asym</code></td>
<td>
<p>a numeric parameter representing the asymptote.</p>
</td></tr>
<tr valign="top"><td><code>xmid</code></td>
<td>
<p>a numeric parameter representing the <code>x</code> value at the
inflection point of the curve. The value of <code>SSlogis</code> will be
<code>Asym/2</code> at <code>xmid</code>.</p>
</td></tr>
<tr valign="top"><td><code>scal</code></td>
<td>
<p>a numeric scale parameter on the <code>input</code> axis.</p>
</td></tr>
</table>
<h3>Value</h3>
<p>a numeric vector of the same length as <code>input</code>. It is the value of
the expression <code>Asym/(1+exp((xmid-input)/scal))</code>. If all of
the arguments <code>Asym</code>, <code>xmid</code>, and <code>scal</code> are
names of objects the gradient matrix with respect to these names is attached as
an attribute named <code>gradient</code>.
</p>
<h3>Author(s)</h3>
<p>José Pinheiro and Douglas Bates</p>
<h3>See Also</h3>
<p><code>nls</code>, <code>selfStart</code>
</p>
<h3>Examples</h3>
<pre>
Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ]
SSlogis(Chick.1$Time, 368, 14, 6) # response only
Asym <- 368; xmid <- 14; scal <- 6
SSlogis(Chick.1$Time, Asym, xmid, scal) # response and gradient
getInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)
## Initial values are in fact the converged values
fm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1)
summary(fm1)
</pre>
</body></html>