Description Methods See Also Examples

Methods for sampling in compact strata.

- x = "CompactStratification", n = "missing", type = "missing"
samples the centroids of each stratum.

- x = "CompactStratification", n = "numeric", type = "missing"
stratified simple random sampling with

*n*samples per stratum.- x = "CompactStratificationEqualArea", n = "numeric", type = "character"
if

`type = "composite"`

, stratified simple random sampling of*n*composites.- x = "CompactStratificationPriorPoints", n = "missing", type = "missing"
spatial infill sampling

`stratify`

for stratification, `spsample`

for other types of spatial sampling, and `estimate`

for inference.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
# Note: the example below requires the 'rgdal'-package.
# You may consider the 'maptools'-package as an alternative
if (require(rgdal)) {
# read a vector representation of the `Farmsum' field
shpFarmsum <- readOGR(
dsn = system.file("maps", package = "spcosa"),
layer = "farmsum"
)
# stratify `Farmsum' into 50 strata
# NB: increase argument 'nTry' to get better results
set.seed(314)
myStratification <- stratify(shpFarmsum, nStrata = 50, nTry = 1)
# sample two sampling units per stratum
mySamplingPattern <- spsample(myStratification, n = 2)
# plot the resulting sampling pattern on
# top of the stratification
plot(myStratification, mySamplingPattern)
}
``` |

spcosa documentation built on April 1, 2018, 12:05 p.m.

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