blockMatrixDiagonal: diagonal block matrix
In samplingDataCRT: Sampling Data Within Different Study Designs for Cluster Randomized Trials
Description
Usage
Arguments
Value
Examples
View source: R/blockMatrixDiagonal.R
Description
create a diagonal block matrix
Usage
1
Arguments
...
a list of matrices
Value
diagonal block matrix concatinated from this list of matrices
Examples
1
2
3
4
5
6
7
8
9
10
11
m1<-matrix(round(runif(4*4),1),nrow=4,ncol=4)
m2<-matrix(round(runif(4*4),1),nrow=4,ncol=4)
blockMatrixDiagonal(m1,m2,m2,m1)
sigma.1<-0.1
sigma.2<-0.4
J<-10 #subjects
I<-3 #cluster
V.i<-sigma.2*matrix(1,nrow=J,ncol=J)+sigma.1*diag(1, nrow=J,ncol=J) #Covarianmatrix of one cluster
x<-lapply(1:I, function(X) V.i)
blockMatrixDiagonal(x) #Covarianmatrix of all cluster
Example output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.1 0.0 0.2 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[2,] 0.2 0.1 0.2 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[3,] 0.5 0.3 0.9 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[4,] 0.9 0.1 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[5,] 0.0 0.0 0.0 0.0 0.5 0.4 0.0 1.0 0.0 0.0 0.0 0.0 0.0
[6,] 0.0 0.0 0.0 0.0 0.1 0.1 0.5 0.9 0.0 0.0 0.0 0.0 0.0
[7,] 0.0 0.0 0.0 0.0 0.9 0.3 0.8 0.7 0.0 0.0 0.0 0.0 0.0
[8,] 0.0 0.0 0.0 0.0 0.1 0.0 0.9 0.3 0.0 0.0 0.0 0.0 0.0
[9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4 0.0 1.0 0.0
[10,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.5 0.9 0.0
[11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.3 0.8 0.7 0.0
[12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.9 0.3 0.0
[13,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
[14,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
[15,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5
[16,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9
[,14] [,15] [,16]
[1,] 0.0 0.0 0.0
[2,] 0.0 0.0 0.0
[3,] 0.0 0.0 0.0
[4,] 0.0 0.0 0.0
[5,] 0.0 0.0 0.0
[6,] 0.0 0.0 0.0
[7,] 0.0 0.0 0.0
[8,] 0.0 0.0 0.0
[9,] 0.0 0.0 0.0
[10,] 0.0 0.0 0.0
[11,] 0.0 0.0 0.0
[12,] 0.0 0.0 0.0
[13,] 0.0 0.2 0.5
[14,] 0.1 0.2 0.3
[15,] 0.3 0.9 0.8
[16,] 0.1 0.7 0.0
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[2,] 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[3,] 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[4,] 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[5,] 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[6,] 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[7,] 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.0 0.0 0.0
[8,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.0 0.0 0.0
[9,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.0 0.0 0.0
[10,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.0 0.0 0.0
[11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4 0.4
[12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.5 0.4
[13,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.5
[14,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[15,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[16,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[17,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[18,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[19,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[20,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[21,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[22,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[23,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[24,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[25,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[26,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[27,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[28,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[29,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[30,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[2,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[3,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[4,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[5,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[6,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[7,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[10,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[11,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[12,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[13,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[14,] 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[15,] 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[16,] 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[17,] 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[18,] 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[19,] 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.0 0.0 0.0 0.0 0.0
[20,] 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.0 0.0 0.0 0.0 0.0
[21,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4 0.4 0.4 0.4
[22,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.5 0.4 0.4 0.4
[23,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.5 0.4 0.4
[24,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.5 0.4
[25,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.5
[26,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[27,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[28,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[29,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[30,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[,26] [,27] [,28] [,29] [,30]
[1,] 0.0 0.0 0.0 0.0 0.0
[2,] 0.0 0.0 0.0 0.0 0.0
[3,] 0.0 0.0 0.0 0.0 0.0
[4,] 0.0 0.0 0.0 0.0 0.0
[5,] 0.0 0.0 0.0 0.0 0.0
[6,] 0.0 0.0 0.0 0.0 0.0
[7,] 0.0 0.0 0.0 0.0 0.0
[8,] 0.0 0.0 0.0 0.0 0.0
[9,] 0.0 0.0 0.0 0.0 0.0
[10,] 0.0 0.0 0.0 0.0 0.0
[11,] 0.0 0.0 0.0 0.0 0.0
[12,] 0.0 0.0 0.0 0.0 0.0
[13,] 0.0 0.0 0.0 0.0 0.0
[14,] 0.0 0.0 0.0 0.0 0.0
[15,] 0.0 0.0 0.0 0.0 0.0
[16,] 0.0 0.0 0.0 0.0 0.0
[17,] 0.0 0.0 0.0 0.0 0.0
[18,] 0.0 0.0 0.0 0.0 0.0
[19,] 0.0 0.0 0.0 0.0 0.0
[20,] 0.0 0.0 0.0 0.0 0.0
[21,] 0.4 0.4 0.4 0.4 0.4
[22,] 0.4 0.4 0.4 0.4 0.4
[23,] 0.4 0.4 0.4 0.4 0.4
[24,] 0.4 0.4 0.4 0.4 0.4
[25,] 0.4 0.4 0.4 0.4 0.4
[26,] 0.5 0.4 0.4 0.4 0.4
[27,] 0.4 0.5 0.4 0.4 0.4
[28,] 0.4 0.4 0.5 0.4 0.4
[29,] 0.4 0.4 0.4 0.5 0.4
[30,] 0.4 0.4 0.4 0.4 0.5
samplingDataCRT documentation built on May 2, 2019, 9:25 a.m.
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Description Usage Arguments Value Examples
View source: R/blockMatrixDiagonal.R
Description
create a diagonal block matrix
Usage
1 |
Arguments
... |
a list of matrices |
Value
diagonal block matrix concatinated from this list of matrices
Examples
1 2 3 4 5 6 7 8 9 10 11 | m1<-matrix(round(runif(4*4),1),nrow=4,ncol=4)
m2<-matrix(round(runif(4*4),1),nrow=4,ncol=4)
blockMatrixDiagonal(m1,m2,m2,m1)
sigma.1<-0.1
sigma.2<-0.4
J<-10 #subjects
I<-3 #cluster
V.i<-sigma.2*matrix(1,nrow=J,ncol=J)+sigma.1*diag(1, nrow=J,ncol=J) #Covarianmatrix of one cluster
x<-lapply(1:I, function(X) V.i)
blockMatrixDiagonal(x) #Covarianmatrix of all cluster
|
Example output
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.1 0.0 0.2 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[2,] 0.2 0.1 0.2 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[3,] 0.5 0.3 0.9 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[4,] 0.9 0.1 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[5,] 0.0 0.0 0.0 0.0 0.5 0.4 0.0 1.0 0.0 0.0 0.0 0.0 0.0
[6,] 0.0 0.0 0.0 0.0 0.1 0.1 0.5 0.9 0.0 0.0 0.0 0.0 0.0
[7,] 0.0 0.0 0.0 0.0 0.9 0.3 0.8 0.7 0.0 0.0 0.0 0.0 0.0
[8,] 0.0 0.0 0.0 0.0 0.1 0.0 0.9 0.3 0.0 0.0 0.0 0.0 0.0
[9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4 0.0 1.0 0.0
[10,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.5 0.9 0.0
[11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.3 0.8 0.7 0.0
[12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.9 0.3 0.0
[13,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1
[14,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2
[15,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5
[16,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9
[,14] [,15] [,16]
[1,] 0.0 0.0 0.0
[2,] 0.0 0.0 0.0
[3,] 0.0 0.0 0.0
[4,] 0.0 0.0 0.0
[5,] 0.0 0.0 0.0
[6,] 0.0 0.0 0.0
[7,] 0.0 0.0 0.0
[8,] 0.0 0.0 0.0
[9,] 0.0 0.0 0.0
[10,] 0.0 0.0 0.0
[11,] 0.0 0.0 0.0
[12,] 0.0 0.0 0.0
[13,] 0.0 0.2 0.5
[14,] 0.1 0.2 0.3
[15,] 0.3 0.9 0.8
[16,] 0.1 0.7 0.0
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[2,] 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[3,] 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[4,] 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[5,] 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[6,] 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.0 0.0 0.0
[7,] 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.0 0.0 0.0
[8,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.0 0.0 0.0
[9,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.0 0.0 0.0
[10,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.0 0.0 0.0
[11,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4 0.4
[12,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.5 0.4
[13,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.5
[14,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[15,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[16,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[17,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[18,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[19,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[20,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4
[21,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[22,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[23,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[24,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[25,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[26,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[27,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[28,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[29,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[30,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[2,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[3,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[4,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[5,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[6,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[7,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[8,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[9,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[10,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
[11,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[12,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[13,] 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[14,] 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[15,] 0.4 0.5 0.4 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[16,] 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[17,] 0.4 0.4 0.4 0.5 0.4 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[18,] 0.4 0.4 0.4 0.4 0.5 0.4 0.4 0.0 0.0 0.0 0.0 0.0
[19,] 0.4 0.4 0.4 0.4 0.4 0.5 0.4 0.0 0.0 0.0 0.0 0.0
[20,] 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.0 0.0 0.0 0.0 0.0
[21,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.4 0.4 0.4 0.4
[22,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.5 0.4 0.4 0.4
[23,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.5 0.4 0.4
[24,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.5 0.4
[25,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.5
[26,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[27,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[28,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[29,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[30,] 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.4 0.4 0.4
[,26] [,27] [,28] [,29] [,30]
[1,] 0.0 0.0 0.0 0.0 0.0
[2,] 0.0 0.0 0.0 0.0 0.0
[3,] 0.0 0.0 0.0 0.0 0.0
[4,] 0.0 0.0 0.0 0.0 0.0
[5,] 0.0 0.0 0.0 0.0 0.0
[6,] 0.0 0.0 0.0 0.0 0.0
[7,] 0.0 0.0 0.0 0.0 0.0
[8,] 0.0 0.0 0.0 0.0 0.0
[9,] 0.0 0.0 0.0 0.0 0.0
[10,] 0.0 0.0 0.0 0.0 0.0
[11,] 0.0 0.0 0.0 0.0 0.0
[12,] 0.0 0.0 0.0 0.0 0.0
[13,] 0.0 0.0 0.0 0.0 0.0
[14,] 0.0 0.0 0.0 0.0 0.0
[15,] 0.0 0.0 0.0 0.0 0.0
[16,] 0.0 0.0 0.0 0.0 0.0
[17,] 0.0 0.0 0.0 0.0 0.0
[18,] 0.0 0.0 0.0 0.0 0.0
[19,] 0.0 0.0 0.0 0.0 0.0
[20,] 0.0 0.0 0.0 0.0 0.0
[21,] 0.4 0.4 0.4 0.4 0.4
[22,] 0.4 0.4 0.4 0.4 0.4
[23,] 0.4 0.4 0.4 0.4 0.4
[24,] 0.4 0.4 0.4 0.4 0.4
[25,] 0.4 0.4 0.4 0.4 0.4
[26,] 0.5 0.4 0.4 0.4 0.4
[27,] 0.4 0.5 0.4 0.4 0.4
[28,] 0.4 0.4 0.5 0.4 0.4
[29,] 0.4 0.4 0.4 0.5 0.4
[30,] 0.4 0.4 0.4 0.4 0.5
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