bounds.corr.GSC.NNP {PoisNonNor}

Computes the approximate lower and upper bounds of the correlation matrix entries for the continuous-count pairs

Description

This function calculates the approximate lower and upper bounds for all continuous-count pairs by the method in Demirtas and Hedeker (2011).

Usage

bounds.corr.GSC.NNP(lamvec, pmat)

Arguments

lamvec

a vector of lambda values of length n1.

pmat

a n2x4 matrix where each row includes the four coefficients (a,b,c,d) of the Fleishman's system.

Details

The approximate correlation bounds are computed via the 'Generate, Sort, and Correlate' (GSC) technique, proposed by Demirtas and Hedeker (2011).

Value

Returns a list with two components, both are matrices of size n1xn2 where n1 and n2 are the number of count and continuous variables, respectively.

min

lower correlation bound matrix

max

upper correlation bound matrix

References

Demirtas, H. and Hedeker, D. (2011). A practical way for computing approximate lower and upper correlation bounds. The American Statistician, 65(2), 104-109.

See Also

bounds.corr.GSC.NN, bounds.corr.GSC.PP

Examples

## Not run: 
pmat = matrix(c(
   0.1148643, 1.0899150, -0.1148643, -0.0356926,
  -0.0488138, 0.9203374,  0.0488138,  0.0251256,
  -0.2107427, 1.0398224,  0.2107427, -0.0293247), nrow=3, byrow=TRUE)

lamvec = c(0.5,0.7,0.9)

bounds.corr.GSC.NNP(lamvec,pmat) 

## End(Not run)