| MixfMRI Control {MixfMRI} | R Documentation |
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().