# BHBootCor

0th

Percentile

##### Benjamini & Hochberg (1995)'s procedure for correlation testing with bootstrap evaluation of p-values.

Benjamini & Hochberg (1995)'s procedure on the correlation matrix entries with bootstrap evaluation of p-values (no theoretical proof of control).

##### Usage
BHBootCor(data, alpha = 0.05, stat_test = "gaussian", Nboot = 100,
vect = FALSE)
##### Arguments
data

matrix of observations

alpha

level of multiple testing

stat_test
'empirical'

$\sqrt{n}*abs(corr)$

'fisher'

$\sqrt{n-3}*1/2*\log( (1+corr)/(1-corr) )$

'student'

$\sqrt{n-2}*abs(corr)/\sqrt(1-corr^2)$

'gaussian'

$\sqrt{n}*mean(Y)/sd(Y)$ with $Y=(X_i-mean(X_i))(X_j-mean(X_j))$

Nboot

number of iterations for bootstrap quantile evaluation

vect

if TRUE returns a vector of TRUE/FALSE values, corresponding to vectorize(cor(data)); if FALSE, returns an array containing rows and columns of significative correlations

##### Value

Returns

• a vector containing indexes $\lbrace(i,j),\,i<j\rbrace$ for which correlation between variables $i$ and $j$ is significative, if vect=FALSE.

##### References

Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the royal statistical society. Series B (Methodological), 289-300.

ApplyFdrCor, BHCor

• BHBootCor
##### Examples
# NOT RUN {

n <- 100
p <- 10
corr_theo <- diag(1,p)
data <- MASS::mvrnorm(n,rep(0,p),corr_theo)
alpha <- 0.05
res <- BHBootCor(data,alpha,stat_test='empirical')
# }

Documentation reproduced from package TestCor, version 0.0.0.9, License: GPL (>= 2)

### Community examples

Looks like there are no examples yet.