cor.confint {GeneNT}R Documentation

Asymptotic confidence intervals of Pearson correlation coefficient

Description

This function returns confidence intervals for a list of Pearson correlation estimates given a sample size N and significant level alpha.

Usage

cor.confint(cor, N, alpha)

Arguments

cor Pearson correlation coefficient estimate, can be single value or vector.
N Sample size.
alpha The significant level

Details

The function use Fisher transformation to approximate p-values and confidence intervals.

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://dongxiaozhu.googlepages.com/home)

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). J Comput Biol.

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

See Also

kendall.confint

Examples

## simulate a vector of correlation coefficients 
cor <- runif(20, -1, 1) 
g6 <- cor.confint(cor, 20, 0.05)
g6$conf.int1
g6$conf.int2

[Package GeneNT version 1.4 Index]