Given m vector distributions of length N, creates a single vector distribution consisting of n mixture distributions mixing the m vectors.

mixturiseVector(vecdists, weights = "uniform")

## Arguments

vecdists

(list())
List of VectorDistributions, should be of same length and with the non-`distlist' constructor with the same distribution.

weights

(character(1)|numeric())
Weights passed to MixtureDistribution. Default uniform weighting.

## Details

Let $$v1 = (D11, D12,...,D1N)$$ and $$v2 = (D21, D22,...,D2N)$$ then the mixturiseVector function creates the vector distribution $$v3 = (D31, D32, ..., D3N)$$ where D3N = m(D1N, D2N, wN) where m is a mixture distribution with weights wN.

## Examples

if (FALSE) { # \dontrun{
v1 <- VectorDistribution$new(distribution = "Binomial", params = data.frame(size = 1:2)) v2 <- VectorDistribution$new(distribution = "Binomial", params = data.frame(size = 3:4))
mv1 <- mixturiseVector(list(v1, v2))

# equivalently
mv2 <- VectorDistribution$new(list( MixtureDistribution$new(distribution = "Binomial", params = data.frame(size = c(1, 3))),
MixtureDistribution$new(distribution = "Binomial", params = data.frame(size = c(2, 4))) )) mv1$pdf(1:5)
mv2\$pdf(1:5)
} # }