Vectorizes an array of array-valued observations into a matrix so that each column of the matrix corresponds to a single observational unit.
Array of an order at least two with the last dimension corresponding to the sampling units.
Vectorizes a p_1 x p_2 x ... x p_r x n-dimensional array into a p_1 p_2 ... p_r x n-dimensional matrix, each column of which then corresponds to a single observational unit. The vectorization is done so that the rth index goes through its cycle the fastest and the first index the slowest.
Note that the output is a matrix of the size "number of variables" x "number of observations", that is, a transpose of the standard format for a data matrix.
Matrix whose columns contain the vectorized observed tensors.
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# Generate sample data. n <- 100 x <- t(cbind(rnorm(n, mean = 0), rnorm(n, mean = 1), rnorm(n, mean = 2), rnorm(n, mean = 3), rnorm(n, mean = 4), rnorm(n, mean = 5))) dim(x) <- c(3, 2, n) # Matrix of vectorized observations. vecx <- tensorVectorize(x) # The covariance matrix of individual tensor elements cov(t(vecx))
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