View source: R/components.iva.R
components.iva | R Documentation |
Returns the estimated source components of object of class "iva"
.
components.iva(object, which.dataset = NA, ...)
object |
an object of class |
which.dataset |
positive integer. Provides the index in case the unmixing matrix only for a specific data set is desired. Default is to return all unmixing matrices. |
... |
further arguments are not used. |
Returns the estimated source components for all datasets or only for the requested dataset.
Estimated source components for requested dataset or for all datasets of the object of class "iva"
. If a single dataset is requested, it is an array with dimension [P, N]
and if all datasets are requested, it is an array with dimension [P, N, D]
.
Mika Sipilä
NewtonIVA
, fastIVA
if (require("LaplacesDemon")) { # Generate sources from multivariate Laplace distribution P <- 4; N <- 1000; D <- 4; S <- array(NA, c(P, N, D)) for (i in 1:P) { U <- array(rnorm(D * D), c(D, D)) Sigma <- crossprod(U) S[i, , ] <- rmvl(N, rep(0, D), Sigma) } # Generate mixing matrices from standard normal distribution A <- array(rnorm(P * P * D), c(P, P, D)) # Generate mixtures X <- array(NaN, c(P, N, D)) for (d in 1:D) { X[, , d] <- A[, , d] %*% S[, , d] } # Estimate sources and unmixing matrices res_G <- NewtonIVA(X, source_density = "gaussian") # Source estimates for all D datasets components.iva(res_G) # Source estimates for the second dataset components.iva(res_G, 2) }
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