# contord

0th

Percentile

##### Correlations of discretized variables

The function computes the correlation matrix of the $k$ variables, with given marginal distributions, derived discretizing a $k$-variate standard normal variable with given correlation matrix

Keywords
multivariate, models, distribution, htest, datagen
##### Usage
contord(marginal, Sigma, support = list(), Spearman = FALSE)
##### Arguments
marginal
a list of $k$ elements, where $k$ is the number of variables. The $i$-th element of marginal is the vector of the cumulative probabilities defining the marginal distribution of the $i$-th component of the multivariate variable. If the $i$-th component can take $k_i$ values, the $i$-th element of marginal will contain $k_i-1$ probabilities (the $k_i$-th is obviously 1 and shall not be included).
Sigma
the correlation matrix of the standard multivariate normal variable
support
a list of $k$ elements, where $k$ is the number of variables. The $i$-th element of support is the vector containing the ordered values of the support of the $i$-th variable. By default, the support of the $i$-th variable is $1,2,...,k_i$
Spearman
if TRUE, the function finds Spearman's correlations (and it is not necessary to provide support), if FALSE (default) Pearson's correlations
##### Value

the correlation matrix of the discretized variables

ordcont, ordsample, corrcheck

• contord
##### Examples
# consider 4 discrete variables
k <- 4
# with these marginal distributions
marginal <- list(0.4,c(0.3,0.6), c(0.25,0.5,0.75), c(0.1,0.2,0.8,0.9))
# generated discretizing a multivariate standard normal variable
# with correlation matrix
Sigma <- matrix(0.5,4,4)
diag(Sigma) <- 1
# the resulting correlation matrix for the discrete variables is
contord(marginal, Sigma)
# note all the correlations are smaller than the original 0.6
# change Sigma, adding a negative correlation
Sigma[1,2] <- -0.15
Sigma[2,1] <- Sigma[1,2]
Sigma
# checking whether Sigma is still positive definite
eigen(Sigma)\$values # all >0, OK
contord(marginal, Sigma)

Documentation reproduced from package GenOrd, version 1.4.0, License: GPL

### Community examples

Looks like there are no examples yet.