PCAimpute {MatrixCorrelation} | R Documentation |
Imputation of missing data, NA, using Principal Component Analysis with iterative refitting and mean value updates. The chosen number of components and convergence parameters (iterations and tolerance) influence the precision of the imputation.
PCAimpute(X, ncomp, center = TRUE, max_iter = 20, tol = 10^-5)
X |
|
ncomp |
|
center |
|
max_iter |
|
tol |
|
Final singular value decomposition, imputed X
matrix and
convergence metrics (sequence of sum of squared change and number of iterations).
X <- matrix(rnorm(12),3,4)
X[c(2,6,10)] <- NA
PCAimpute(X, 3)