View source: R/F_plotApproxCovar.R
plotApproxCovar | R Documentation |
Plot an approximation of the correlation structure of the test statistics
plotApproxCovar(
reconsiFit,
col = colorRampPalette(c("yellow", "blue"))(12),
x = seq(-4.2, 4.2, 0.1),
y = seq(-4.2, 4.2, 0.1),
xlab = "Z-values",
ylab = "Z-values",
nBins = 82L,
binEdges = c(-4.1, 4.1),
...
)
reconsiFit |
The reconsi fit |
col, x, y, xlab, ylab, ... |
A list of arguments for the image() function. |
nBins, binEdges |
passed on to the getApproxCovar function |
By default, yellow indicates negative correlaton between bin counts, blue positive correlation
invisible()
This is not the covariance matrix of the p test statistic, nor of the data! It is an approximate covariance matrix of binned test statistics for visualization purposes. See plotCovar for the full covariance matrix.
plotCovar, getApproxCovar
p = 200; n = 50; B = 5e1
x = rep(c(0,1), each = n/2)
mat = cbind(
matrix(rnorm(n*p/10, mean = 5+x),n,p/10), #DA
matrix(rnorm(n*p*9/10, mean = 5),n,p*9/10) #Non DA
)
mat = mat = mat + rnorm(n, sd = 0.3) #Introduce some dependence
fdrRes = reconsi(mat, x, B = B)
plotApproxCovar(fdrRes)
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