sFIR

Estimate response function for each person using smoothed Finite Impulse Response.

internal

Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.

KM Gates

gimme

Group Iterative Multiple Model Estimation

sFIR function

<dl><dt>data</dt>
<dd>The data to be used to estimate response function</dd>
<dt>stimuli</dt>
<dd>A vector containing '0' when the stimuli of interest is not present 
and '1' otherwise. Number of observations across time must equal the length of data.</dd>
<dt>interval</dt>
<dd>Time between observations; for fMRI this is the repetition time. 
Defaults to 1.</dd></dl>

Arguments

Estimate response function for each person using smoothed Finite Impulse Response. — sFIR

<dl>

<dt>data</dt>
<dd>The data to be used to estimate response function</dd>


<dt>stimuli</dt>
<dd>A vector containing '0' when the stimuli of interest is not present 
and '1' otherwise. Number of observations across time must equal the length of data.</dd>


<dt>interval</dt>
<dd>Time between observations; for fMRI this is the repetition time. 
Defaults to 1.</dd>

</dl>

sFIR: Estimate response function for each person using smoothed Finite Impulse Response.

Description

Usage

Value

Arguments