R: Diagnostic F Statistics Visualization

diagnosticPlot {biclust} | R Documentation

## Diagnostic F Statistics Visualization

### Description

Plots distributions of bootstrap replicates of F-statistics for row and column effect and highlights the observed statistics

### Usage

    diagnosticPlot(bootstrapOutput)

### Arguments

`bootstrapOutput` | output of `diagnoseColRow` function, containing bootstrap replicates and observed F-statistics

### Value

No value is returned. The plot is constructed in a current device.

### Author(s)

Tatsiana KHAMIAKOVA tatsiana.khamiakova@uhasselt.be

### See Also

`diagnoseColRow`, `computeObservedFstat`

### Examples

    #---simulate dataset with 1 bicluster ---#
    xmat<-matrix(rnorm(20*50,0,0.25),50,50) # background noise only
    rowSize <- 20 #number of rows in a bicluster
    colSize <- 10 #number of columns in a bicluster
    a1<-rnorm(rowSize,1,0.1) #sample row effect from N(0,0.1) #adding a coherent values bicluster:
    b1<-rnorm((colSize),2,0.25)  #sample column effect from N(0,0.05)
    mu<-0.01 #constant value signal
     for ( i in 1 : rowSize){
     	for(j in 1: (colSize)){
     		xmat[i,j] <- xmat[i,j] + mu + a1[i] + b1[j]
     	}
     }
     #--obtain a bicluster by running an algorithm---#
    plaidmab <- biclust(x=xmat, method=BCPlaid(), cluster="b", fit.model = y ~ m + a+ b,
    background = TRUE, row.release = 0.6, col.release = 0.7, shuffle = 50, back.fit = 5,
    max.layers = 1, iter.startup = 100, iter.layer = 100, verbose = TRUE)

    #Run bootsrap procedure:
    Bootstrap <- diagnoseColRow(x=xmat, bicResult = plaidmab, number = 1,
      nResamplings = 999, replace = TRUE)

    # plotting distribution of bootstrap replicates
    diagnosticPlot(bootstrapOutput = Bootstrap)

[Package biclust version 2.0.2 Index]