11_d_control: Sets of controls in MixfMRI

In MixfMRI: Mixture fMRI Clustering Analysis

Sets of controls in MixfMRI

Description

These sets of controls are used to provide default values in this package.

Format

Objects contain several parameters for methods.

Details

The elements of .FC.CT are default values for main controls of MixfMRI including

Elements	Default	Usage
algorithm	"apecma"	implemented algorithm
optim.method	"BFGS"	optimization method
model.X	"I"	cov matrix structure
ignore.X	FALSE	if using voxel information
check.X.unit	TRUE	if checking X in [0, 1]
CONTROL	a list	see CONTROL next for details
INIT	a list	see INIT next for details
LRT	a list	see LRT next for details
MPI.gbd	FALSE	if MPI speedup available
common.gbd	TRUE	if X in common gbd format

The elements of CONTROL are default values for optimization controls of implemented EM algorithm including

Elements	Default	Usage
max.iter	1000	maximum number of EM iterations
abs.err	1e-4	absolute error of convergence
rel.err	1e-6	relative error of convergence
debug	1	debugging level
RndEM.iter	10	RndEM iterations
exp.min	log(.Machine$double.xmin)	minimum exponential power
exp.max	log(.Machine$double.xmax)	maximum exponential power
sigma.ill	1e-6	ill condition limit
DS.max	1e+4	maximum chol() cov matrix
DS.min	1e-6	minimum chol() cov matrix

The elements of INIT are default values or limitations for initial parameters implemented for EM algorithm including

Elements	Default	Usage
min.1st.prop	0.8	minimum proportion of 1st cluster
max.PV	0.1	maximum p-value for initialization
BETA.alpha.min	0 + 1e-6	minimum value of alpha parameter of Beta distribution
BETA.alpha.max	1 - 1e-6	maximum value of alpha parameter of Beta distribution
BETA.beta.min	1 + 1e-6	minimum value of beta parameter of Beta distribution
BETA.beta.max	1e+6	maximum value of beta parameter of Beta distribution
max.try.iter	10	maximum retry iterations if result is unstable
class.method	"prob.extned"	classification method at initializations

The elements of LRT are default values or limitations for likelihood ratio tests including

Elements	Default	Usage
H0.alpha	1	null hypothesis alpha parameter of Beta distribution
H0.beta	1	null hypothesis beta parameter of Beta distribution
H0.mean	0.05	null hypothesis mean of Beta distribution

Author(s)

Wei-Chen Chen and Ranjan Maitra.

References

Chen, W.-C. and Maitra, R. (2021) “A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies”, arXiv:2102.03639.

See Also

set.global(), fclust().

MixfMRI documentation built on Sept. 8, 2023, 5:06 p.m.