# corrcheck

0th

Percentile

##### Checking correlations

Function $corrcheck$ returns the lower and upper bounds of the correlation coefficients of the ordinal/discrete variables given their marginal distributions, i.e. returns the range of feasible pairwise correlations.

Keywords
models, distribution, htest
##### Usage
corrcheck(marginal, 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 h
support
a list of $k$ elements, where $k$ is the number of variables. The $i$-th element of support contains 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
TRUE if we consider Spearman's correlation, FALSE (default) if we consider Pearson's correlation
##### Value

• The functions returns a list of two matrices: the former contains the lower bounds, the latter the upper bounds of the feasible correlations (on the extra-diagonal elements)

contord, ordcont, ordsample

• corrcheck
##### Examples
# four variables
k<-4
# with 2, 3, 4, and 5 categories (Likert scales, by default)
kj<-c(2,3,4,5)
# and these marginal distributions (set of cumulative probabilities)
marginal<-list(0.4,c(0.6,0.9),c(0.1,0.2,0.4),c(0.6,0.7,0.8,0.9))
corrcheck(marginal) # lower and upper bounds for Pearson's rho
corrcheck(marginal,Spearman=TRUE) # lower and upper bounds for Spearman's rho
# change the support
support<-list(c(0,1),c(1,2,4),c(1,2,3,4),c(0,1,2,5,10))
corrcheck(marginal, support=support) # updated bounds
Documentation reproduced from package GenOrd, version 1.0.1, License: GPL

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