TestCor (version 0.0.0.9)

BonferroniCor_SD: Bonferroni multiple testing method for correlations with stepdown procedure.

Description

Bonferroni multiple testing method for correlations with stepdown procedure.

Usage

BonferroniCor_SD(data, alpha, stat_test = "empirical", 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 \(Y=(X_i-mean(X_i))(X_j-mean(X_j))\)

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

Bonferroni, C. E. (1935). Il calcolo delle assicurazioni su gruppi di teste. Studi in onore del professore salvatore ortu carboni, 13-60.

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.

See Also

ApplyFwerCor, BonferroniCor

Examples

Run this code
# NOT RUN {
 
n <- 100
p <- 10
corr_theo <- diag(1,p)
data <- MASS::mvrnorm(n,rep(0,p),corr_theo)
alpha <- 0.05
res <- BonferroniCor_SD(data,alpha,stat_test='empirical')
# }

Run the code above in your browser using DataCamp Workspace