pcor.confint {GeneNT}R Documentation

Asymptotic confidence intervals of partial correlation coefficient

Description

This function returns confidence intervals for a list of partial correlation coefficients given empirical sample size kappa and significant level alpha.

Usage

pcor.confint(pcor, kappa, alpha)

Arguments

pcor Partial correlation coefficient(s)
kappa Empirical sample size
alpha The significant level

Details

For details about the empirical sample size, refer to Schäfer, J., and K. Strimmer, 2004, Bioinformatics, 1:1-13. Briefly, it refers sample size that are estimated from data using a two-component mixture model rather than from sample size in the situation of "small N, large p" in the Gaussian Graphic Model framework.

Value

The function returns asymptotic lower and upper bound(s) of Pearson correlation coefficient(s).

conf.int1 Lower bound(s) of Pearson correlation coefficient(s)
conf.int2 Upper bound(s) of Pearson correlation coefficient(s)

Author(s)

Dongxiao Zhu (http://www-personal.umich.edu/~zhud)

References

Zhu, D., Hero, A.O., Qin, Z.S. and Swaroop, A. High throughput screening of co-expressed gene pairs with controlled False Discovery Rate (FDR) and Minimum Acceptable Strength (MAS). Submitted.

Schäfer, J., and K. Strimmer. (2004) An empirical Bayes approach to inferring large-scale gene association networks. Bioinformatics, 1, 1-13.

See Also

cor.confint

Examples

pcor <- runif(20, -1, 1) #simulate a vector of correlation coefficients 
#g7 <- pcor.confint(pcor, 20, 0.05)
#g7$conf.int1
#g7$conf.int2

[Package GeneNT version 1.2 Index]