exp_fit

This function performs an exponential fit using non-linear least squares (nls).

Analyze data from behavioral experiments conducted using 'MED-PC' software developed by Med Associates Inc.
Includes functions to fit exponential and hyperbolic models for delay discounting tasks, exponential mixtures for
inter-response times, and Gaussian plus ramp models for peak procedure data, among others. For more details, refer to Alcala et al. (2023) <doi:10.31234/osf.io/8aq2j>.

Emmanuel Alcala

YEAB

Analyze Data from Analysis of Behavior Experiments

Rodrigo Sosa

Victor Reyes

exp_fit function

<dl><dt>value</dt>
<dd>A numeric vector of the subjective values (indifference points).</dd>
<dt>delay</dt>
<dd>A numeric vector of the delays used in the experiment.</dd>
<dt>initial_guess</dt>
<dd>A numeric value providing an initial estimate for the parameter <code>k</code>.</dd>
<dt>max_iter</dt>
<dd>An integer specifying the maximum number of iterations for the nls fitting algorithm.
Default is 1e5.</dd>
<dt>scale_offset</dt>
<dd>A numeric value for the scaling offset used in nls fitting control. Default is 0.</dd></dl>

Arguments

Exponential fit with nls — exp_fit

<dl>

<dt>value</dt>
<dd>A numeric vector of the subjective values (indifference points).</dd>


<dt>delay</dt>
<dd>A numeric vector of the delays used in the experiment.</dd>


<dt>initial_guess</dt>
<dd>A numeric value providing an initial estimate for the parameter <code>k</code>.</dd>


<dt>max_iter</dt>
<dd>An integer specifying the maximum number of iterations for the nls fitting algorithm.
Default is 1e5.</dd>


<dt>scale_offset</dt>
<dd>A numeric value for the scaling offset used in nls fitting control. Default is 0.</dd>

</dl>

exp_fit: Exponential fit with nls

Description

Usage

Value

Arguments

Examples