BestFit

This script takes a dark object, a list of parameters and AICc scores from <code>ModelSelect</code> to chose a model and then return optimised values for the parameter estimates. Analysis of the data can be halted here if wished.
However, a <code>MultiStart</code> check can be useful if it is suspected that a local minimum has been found. Furthermore, <code>BootDark</code> will provide confidence intervals for the parameter estimates.

models

regression

utilities

optimization

data

The recovery of visual sensitivity in a dark environment is known
as dark adaptation. In a clinical or research setting the recovery is typically
measured after a dazzling flash of light and can be described by the Mahroo,
Lamb and Pugh (MLP) model of dark adaptation. The functions in this package take
dark adaptation data and use nonlinear regression to find the parameters of the
model that 'best' describe the data. They do this by firstly, generating rapid
initial objective estimates of data adaptation parameters, then a multi-start
algorithm is used to reduce the possibility of a local minimum. There is also a
bootstrap method to calculate parameter confidence intervals. The functions rely
upon a 'dark' list or object. This object is created as the first step in the
workflow and parts of the object are updated as it is processed.

Dr MF Kelly

Dark

The Analysis of Dark Adaptation Data

BestFit function

<dl> <dt>obj</dt>
<dd>A dark object
</dd> <dt>MSC</dt>
<dd>A list from the function <code>ModelSelect</code>
</dd> <dt>draw</dt>
<dd>A flag to indicate whether a figure should be drawn.
</dd></dl>

Arguments

Jeremiah MF Kelly
Mumac Ltd, SK7 6NR, GB

Author


BestFit — BestFit

<dl>

 <dt>obj</dt>
<dd>A dark object
</dd>

 <dt>MSC</dt>
<dd>A list from the function <code>ModelSelect</code>
</dd>

 <dt>draw</dt>
<dd>A flag to indicate whether a figure should be drawn.
</dd>

</dl>

BestFit: BestFit

Description

Usage

Value

Arguments

Author

See Also

Examples