Description Usage Arguments Value Author(s) Examples
View source: R/standard.matrix.R
Given a matrix of support points X and a corresponding vector of probabilities piv it computes the mean for each dimension, the variance covariance matrix, the correlation matrix, Spearman correlation matrix, and the standarized matrix Y
1 | standard.matrix(X,piv)
|
X |
matrix of support points for the distribution included row by row |
piv |
vector of probabilities with the same number of elements as the rows of |
mu |
vector of the means |
V |
variance-covariance matrix |
si2 |
vector of the variances |
si |
vector of standard deviations |
Cor |
Braives-Pearson correlation matrix |
Sper |
Spearman correlation matrix |
Y |
matrix of standardized support points |
Francesco Bartolucci, Silvia Bacci, Michela Gnaldi - University of Perugia (IT)
1 2 3 4 | ## Example of standardization of a randomly generated distribution
X = matrix(rnorm(100),20,5)
piv = runif(20); piv = piv/sum(piv)
out = standard.matrix(X,piv)
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Loading required package: MASS
Loading required package: limSolve
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