.validate_input {BayesDLMfMRI} | R Documentation |
.validate_input
Description
validate input
Usage
.validate_input(
N1 = NULL,
Test = NULL,
Nsimu1 = NULL,
ffdc = NULL,
covariates = NULL,
r1 = NULL,
delta = NULL,
perVol = NULL,
Min.vol = NULL,
n0 = NULL,
Cutpos1 = NULL,
ffdGroup = NULL
)
Arguments
N1 |
is the number of images (2<N1<T) from the ffdc array employed in the model fitting.N1=NULL (or equivalently N1=T) is its default value, taking all the images in the ffdc array for the fitting process. |
Test |
test type either "LTT" (Average cluster effect) or "JointTest" (Joint effect). |
Nsimu1 |
is the number of simulated on-line trajectories related to the state parameters. These simulated curves are later employed to compute the posterior probability of voxel activation. |
ffdc |
a 4D array (ffdc[i,j,k,t]) that contains the sequence of MRI images that are meant to be analyzed. (i,j,k) define the position of the observed voxel at time t. |
covariates |
a data frame or matrix whose columns contain the covariates related to the expected BOLD response obtained from the experimental setup. |
r1 |
a positive integer number that defines the distance from every voxel with its most distant neighbor. This value determines the size of the cluster. The users can set a range of different r values: r = 0, 1, 2, 3, 4, which leads to q = 1, 7, 19, 27, 33, where q is the size of the cluster. |
delta |
a discount factor related to the evolution variances. Recommended values between 0.85<delta<1. delta=1 will yield results similar to the classical general linear model. |
perVol |
helps to define a threshold for the voxels considered in the analysis. For example, Min.vol = 0.10 means that all the voxels with values below to max(ffdc)*perVol can be considered irrelevant and discarded from the analysis. |
Min.vol |
helps to define a threshold for the voxels considered in the analysis. For example, Min.vol = 0.10 means that all the voxels with values below to max(ffdc)*Min.vol can be considered irrelevant and discarded from the analysis. |
n0 |
a positive hyperparameter of the prior distribution for the covariance matrix S0 at t=0 (n=1 is the default value when no prior information is available). For the case of available prior information, n0 can be set as n0=np, where np is the number of MRI images in the pilot sample. |
Cutpos1 |
a cutpoint time from where the on-line trajectories begin. This parameter value is related to an approximation from a t-student distribution to a normal distribution. Values equal to or greater than 30 are recommended (30<Cutpos1<T). |
ffdGroup |
group |