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377d9c8e78829164590150f4030e3fc1136516b4 Seminar 2 ============================
This is setting up a random " rnorm" 10 x 4 matrix: <<<<<<< HEAD
n <- 10
B <- 4
x <- matrix(rnorm(n * B), nrow = n)
x## [,1] [,2] [,3] [,4]
## [1,] -1.05771 -0.10171 0.29128 -1.08420
## [2,] -1.45314 -0.48142 -0.53298 0.03820
## [3,] 2.54016 -0.02761 -0.11140 -0.22346
## [4,] -1.00592 -1.08278 -1.55681 0.57666
## [5,] 0.79305 0.53879 -1.09399 -0.98127
## [6,] -2.81229 1.17569 -0.44606 1.67985
## [7,] 0.34365 0.26845 0.06427 0.30428
## [8,] 1.53223 -2.18819 0.34254 -1.52646
## [9,] -0.49920 0.38954 -0.92183 0.08898
## [10,] -0.05945 -0.56703 -0.63258 -0.67686
To assign names to the rows and columns:
rownames(x) <- sprintf("obs%02d", 1:n)
colnames(x) <- sprintf("samp%02d", 1:B)
x## samp01 samp02 samp03 samp04
## obs01 -1.05771 -0.10171 0.29128 -1.08420
## obs02 -1.45314 -0.48142 -0.53298 0.03820
## obs03 2.54016 -0.02761 -0.11140 -0.22346
## obs04 -1.00592 -1.08278 -1.55681 0.57666
## obs05 0.79305 0.53879 -1.09399 -0.98127
## obs06 -2.81229 1.17569 -0.44606 1.67985
## obs07 0.34365 0.26845 0.06427 0.30428
## obs08 1.53223 -2.18819 0.34254 -1.52646
## obs09 -0.49920 0.38954 -0.92183 0.08898
## obs10 -0.05945 -0.56703 -0.63258 -0.67686
To make plots you can use very easy commands:
colMeans(x)## samp01 samp02 samp03 samp04
## -0.1679 -0.2076 -0.4598 -0.1804
plot(colMeans(x))
If you use the #1 it refers to row, #2 column:
h <- apply(x, 1, mean)Here is another scatter plot of the means of the rows:
plot(h)
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n <- 10
B <- 4
x <- matrix(rnorm(n*B), nrow = n)
x
To assign names to the rows and columns:
rownames(x) <- sprintf("obs%02d", 1:n)
colnames(x) <- sprintf("samp%02d", 1:B)
x
To make plots you can use very easy commands:
colMeans(x)
plot(colMeans(x))
If you use the #1 it refers to row, #2 column:
h <- apply(x, 1, mean)
Here is another scatter plot of the means of the rows:
plot(h)
377d9c8e78829164590150f4030e3fc1136516b4