\(\sqrt{n}*mean(Y)/sd(Y)\) 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
Romano, J. P., & Wolf, M. (2005). Exact and approximate stepdown methods for multiple hypothesis testing. Journal of the American Statistical Association, 100(469), 94-108.
Roux, M. (2018). Graph inference by multiple testing with application to Neuroimaging, Ph.D., Universit<U+00E9> Grenoble Alpes, France, https://tel.archives-ouvertes.fr/tel-01971574v1.
# NOT RUN {
n <- 100
p <- 10
corr_theo <- diag(1,p)
data <- MASS::mvrnorm(n,rep(0,p),corr_theo)
alpha <- 0.05
res <- BootRWCor_SD(data,alpha,stat_test='empirical',Nboot=1000)
# }