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.

See Also

ApplyFdrCor, BHCor

Aliases
  • 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)

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