blocksample: Block sampling

Description Usage Arguments Value Author(s) Examples

View source: R/blocksample.R

Description

Sample blockwise from clustered data

Usage

1
blocksample(data, size, idvar = "id", replace = TRUE, ...)

Arguments

data

Data frame

idvar

Column defining the clusters

size

Size of samples

replace

Logical indicating wether to sample with replacement

...

additional arguments to lower level functions

Value

data.frame

Author(s)

Klaus K. Holst

Examples

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d <- data.frame(x=rnorm(5), z=rnorm(5), id=c(4,10,10,5,5), v=rnorm(5))
(dd <- blocksample(d,size=20))
attributes(dd)$id

## Not run: 
blocksample(data.table::data.table(d),1e6)

## End(Not run)

Example output

Loading required package: timereg
Loading required package: survival
Loading required package: lava
lava version 1.5
mets version 1.2.2
             x          z id           v
5   -1.2431171 -0.5691450  5 -1.08443759
3   -0.3433448  0.1222036 10 -1.28982707
3.1 -0.3433448  0.1222036 10 -1.28982707
2   -3.0635359  0.7011888 10 -1.39236049
1   -0.6195613  0.6724893  4  0.74298009
1.1 -0.6195613  0.6724893  4  0.74298009
5.1 -1.2431171 -0.5691450  5 -1.08443759
2.1 -3.0635359  0.7011888 10 -1.39236049
4    0.5767734 -1.9210679  5  0.03634879
5.2 -1.2431171 -0.5691450  5 -1.08443759
1.2 -0.6195613  0.6724893  4  0.74298009
2.2 -3.0635359  0.7011888 10 -1.39236049
4.1  0.5767734 -1.9210679  5  0.03634879
4.2  0.5767734 -1.9210679  5  0.03634879
2.3 -3.0635359  0.7011888 10 -1.39236049
3.2 -0.3433448  0.1222036 10 -1.28982707
3.3 -0.3433448  0.1222036 10 -1.28982707
5.3 -1.2431171 -0.5691450  5 -1.08443759
3.4 -0.3433448  0.1222036 10 -1.28982707
2.4 -3.0635359  0.7011888 10 -1.39236049
NULL
                  x          z id           v
      1: -0.3433448  0.1222036 10 -1.28982707
      2: -0.6195613  0.6724893  4  0.74298009
      3: -0.6195613  0.6724893  4  0.74298009
      4: -0.6195613  0.6724893  4  0.74298009
      5: -0.6195613  0.6724893  4  0.74298009
     ---                                     
 999996: -3.0635359  0.7011888 10 -1.39236049
 999997: -0.6195613  0.6724893  4  0.74298009
 999998:  0.5767734 -1.9210679  5  0.03634879
 999999: -3.0635359  0.7011888 10 -1.39236049
1000000: -0.3433448  0.1222036 10 -1.28982707
Warning message:
system call failed: Cannot allocate memory 

mets documentation built on May 31, 2017, 1:52 a.m.