cor0.test {GeneTS} R Documentation

## Test of Vanishing (Partial) Correlation

### Description

`cor0.test` computes a p-value for the two-sided test with the null hypothesis H0: rho == 0 versus the alternative hypothesis HA: rho != 0.

If `method="student"` is selected then the statistic `t=r*sqrt((kappa-1)/(1-r*r))` is considered which under H0 is student-t distributed with `df=kappa-1`. This method is exact.

If `method="dcor0"` is selected then the p-value is computed directly from the distribution function `pcor0`. This method is also exact.

If `method="ztransform"` is selected then the p-value is computed using the z-transform (see `z.transform`), i.e. using a suitable chosen normal distribution. This method returns approximate p-values.

### Usage

```cor0.test(r, kappa, method=c("student", "dcor0", "ztransform"))
```

### Arguments

 `r` observed correlation `kappa` degree of freedom of the null-distribution `method` method used to compute the p-value

A p-value.

### Author(s)

Juliane Schaefer (http://www.stat.uni-muenchen.de/~schaefer/) and Korbinian Strimmer (http://www.stat.uni-muenchen.de/~strimmer/).

`dcor0`, `cor0.estimate.kappa`, `kappa2N`, `z.transform`.

### Examples

```# load GeneTS library
library(GeneTS)

# covariance matrix
m.cov <- rbind(
c(3,1,1,0),
c(1,3,0,1),
c(1,0,2,0),
c(0,1,0,2)
)

# compute partial correlations
m.pcor <- cor2pcor(m.cov)
m.pcor

# corresponding p-values
# assuming a sample size of 25, i.e. kappa=22
kappa2N(22, 4)
cor0.test(m.pcor, kappa=22)
cor0.test(m.pcor, kappa=22) < 0.05

# p-values become smaller with larger r
cor0.test(0.7, 12)
cor0.test(0.8, 12)
cor0.test(0.9, 12)

# comparison of various methods
cor0.test(0.2, 45, method="student")
cor0.test(0.2, 45, method="dcor0")
cor0.test(0.2, 45, method="ztransform")
```

[Package GeneTS version 2.3 Index]