# tests.old/minCV_simple_k_test.R In jlisic/saAlloc: Optimal Allocation of Sampling Units to Form Strata using Simulated Annealing

```# this is a test for averaging S^2 (e.g. k > 1)

library(saAlloc)

set.seed(400)

# data set with 100 observations and 4 characteristics split between two strata

x <- matrix(1:16,ncol=4)

label <- c(
0,
0,
0,
0,
0,
1,
1,
1,
0,
0,
0,
1,
1,
1,
1,
1
)

x1 <- c(
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
2,
2,
2,
2,
2,
2
)

x2 <- c(
3,
3,
3,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4,
4,
4
)

x3 <- 1:16

#a <- cbind(x1 + runif(16),x2 + runif(16), x3 + runif(16))
#b <- cbind(x1 + runif(16),x2 + runif(16), x3 + runif(16))

a <- cbind(x1 ,x2 , x3 )
b <- cbind(x1 ,x2 , x3 + label )

colnames(a) <- c('Turtle','Trout','Tuna')
colnames(b) <- c('Turtle','Trout','Tuna')

# interleave a and b
x <- t(matrix( rbind( t(a), t(b)), nrow=ncol(a)))
colnames(x) <- c('Turtle','Trout','Tuna')

# target variance
targetCV <- c(.01,.02,.03)
names(targetCV) <- c('Tuna','Turtle','Trout')

# run minCV
result <- saMinCV(
x,
label+1,
iterations=1,
cooling=0,
targetCV=targetCV,
sampleSize=8
)

#summary(result)
#

truVar <- aggregate(x,
by=list(
rep(label+1,each=2)*100
+ rep(1:2,length(label))
),var)
```
jlisic/saAlloc documentation built on May 5, 2018, 6:36 p.m.