View source: R/analysis_dimReduction_ica.R
performICA | R Documentation |
Perform independent component analysis after processing missing values
performICA(
data,
n.comp = min(5, ncol(data)),
center = TRUE,
scale. = FALSE,
missingValues = round(0.05 * nrow(data)),
alg.typ = c("parallel", "defaltion"),
fun = c("logcosh", "exp"),
alpha = 1,
...
)
data |
an optional data frame (or similar: see
|
n.comp |
number of components to be extracted |
center |
a logical value indicating whether the variables
should be shifted to be zero centered. Alternately, a vector of
length equal the number of columns of |
scale. |
a logical value indicating whether the variables should
be scaled to have unit variance before the analysis takes
place. The default is |
missingValues |
Integer: number of tolerated missing values per column to be replaced with the mean of the values of that same column |
alg.typ |
if |
fun |
the functional form of the |
alpha |
constant in range [1, 2] used in approximation to
neg-entropy when |
... |
Arguments passed on to |
ICA result in a prcomp
object
Other functions to analyse independent components:
plotICA()
performICA(USArrests)
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