# plotApproxCovar: Plot an approximatio of the correlation structure of the test... In reconsi: Resampling Collapsed Null Distributions for Simultaneous Inference

## Description

Plot an approximatio of the correlation structure of the test statistics

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```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), ... ) ```

## Arguments

 `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

## Details

By default, yellow indicates negative correlaton between bin counts, blue positive correlation

invisible()

## Note

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.

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```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) ```

reconsi documentation built on Nov. 8, 2020, 5:04 p.m.