tdcc {ODEsensitivity}

A Measure of Top-Down Correlation

Description

With the use of Savage scores, the Top-Down Correlation Coefficient TDCC compares b rankings.

Usage

tdcc(ranks, pearson = FALSE, plot = FALSE)

Arguments

ranks

[matrix(nrow = b, ncol = k)]
(bxk)-matrix of the ranks of the k variables for each of the b sensitivity analyses, ties are neglected, must be integers.

pearson

[logical(1)]
Should the ordinary Pearson coefficient with Savage scores be computed (b = 2)? Default is FALSE.

plot

[logical(1)]
Should scatter plots showing rankings and Savage scores be created (b = 2)? Default is FALSE.

Details

NOTE: As the implementation of the coefficient of concordance is still defective, please use the Pearson coefficient!

Value

A named vector with components:

• kendall: Coefficient of concordance.

• pearson: Pearson coefficient (only if pearson = TRUE).

Author(s)

Stefan Theers

References

R. L. Iman and W. J. Conover, A Measure of Top-Down Correlation, Technometrics, Vol. 29, No. 3 (Aug., 1987), pp. 351–357.

Examples

# b=2 sensitivity analysis techniques A and B that rate the influence of 
# k=20 variables/ input parameters (example taken from Iman and Conover, 1987):
ranking <- rbind(A = 1:20,
                 B = c(1,3,2,4,16,10,19,12,18,17,
                       20,5,14,7,8,11,6,15,9,13))
tdcc(ranking, pearson = TRUE, plot = TRUE)