processSeed: Process a model using a seed number of regions

In arf3DS4: Activated Region Fitting, fMRI data analysis (3D).

Description

processSeed runs a sequence of models with different starting values to obtain a stable solution. It starts with as simple model with rectangular starts, subsequently it runs a full model given the estimates of the simple model. It then prunes the full model, discarding the regions with bad gradients and/or bounded parameters.

Usage

processSeed(modelname='defaultmodel', seedreg, subject='', 
 condition='', startmethod=c('default','simple'), grad=NULL, 
 bound=NULL, pval=NULL, options=new('options'), pr=T, 
 printlevel=0, try.silen=T, overwrite=T, experiment=NULL)

Arguments

modelname	Name to give the pruned models in the sequence.
seedreg	Number of regions to fit at sequence start (seed number).
subject	Name of the subject.
condition	Name of the condition.
startmethod	Use simple model as start or the default (rectangular method).
grad	Gradient check limits, absolute higher values are pruned.
bound	Threshold to check if a parameter is on a bound. When NULL, check is suppressed.
pval	Prune regions with non-significant Wald statistics higher than pval.
options	Options object.
pr	Output to screen?
printlevel	Number indicating the level of output of the minimization procedure.
try.silen	Should errors be printed when they occur or only passed to the warnings slot.
overwrite	Overwrite the model if a model with the same name already exists?
experiment	Optional experiment object.

Value

Returns the best model (class model)

Author(s)

Wouter D. Weeda - [e-mail]

See Also

model, newModel, fitModel, pruneModel, options, experiment

arf3DS4 documentation built on May 2, 2019, 5:16 p.m.