Description Usage Arguments Value Examples
An R wrapper for carrying out NSMM-ICA on nonparametric multivariate ICA mixture data.
1 2 | EMFASTICAALG(DataMatrix, numCluster, h = 0, maxiter = 300, icaiter = 150,
tol = 1e-06, verb = TRUE, combine = TRUE, seednum = 82196, ...)
|
DataMatrix |
A matrix of which the rows are data entries. Its dimension
is |
numCluster |
Predetermined number of mixing components |
h |
Bandwidth. If |
maxiter |
Maximum number of iterations. Default is |
icaiter |
Maximum number of ICA iterations in each step. Default is
|
tol |
Threshold that defines convergence (of the outer loop). Default
is |
verb |
|
combine |
|
seednum |
Seed number (default is |
The returned value is an EMFASTICAALG
object which consists of a list of items:
$InputData |
A matrix of which the columns are data entries. Its
dimension is |
$Lambdas |
A matrix where rows store estimated mixing weights from each iteration. |
$WMtrs |
List of
|
$WUnmixZ |
List of unmixing matrices for whitened data for each of the m clusters. |
$OriginalSignals |
List of Recovered ICA components for
each of the |
$ProductDensity |
|
$MembershipProbs |
|
$ObjValue |
Vector holding values of data loglikelihood. |
$ICABandWidth |
Matrix holding choices of bandwidth for original signals. |
$call |
The function call that results in the returned object. |
$time |
Computing time elapsed in second. |
1 2 3 | ## An Example that runs the NSMM-ICA algorithm on Cohen's tone data
data(tonedata, package="mixtools")
b <- EMFASTICAALG(tonedata, 2, h=0, tol=1e-8)
|
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