A class for storing a stratification with compact strata.

Objects can be created by calls of the form
`new("CompactStratification", cells, stratumId, centroids, mssd)`

. However, objects are usually
created by calling `stratify`

.

`cells`

:Object of class

`"SpatialPixels"`

, representing the area to be partitioned.`stratumId`

:Object of class

`"integer"`

, indicating to which stratum each cell in`cells`

belong.`centroids`

:Object of class

`"SpatialPoints"`

, representing the centers of gravity of each stratum.`mssd`

:Object of class

`"numeric"`

, representing the mean squared shortest distance.

Class `"Stratification"`

, directly.

- coerce
`signature(from = "CompactStratification", to = "data.frame")`

: coerces to`"data.frame"`

.- coerce
`signature(from = "CompactStratification", to = "SpatialPixels")`

: coerces to`"SpatialPixels"`

.- coerce
`signature(from = "CompactStratification", to = "SpatialPixelsDataFrame")`

: coerces to`"SpatialPixelsDataFrame"`

.- estimate
`signature(statistic = "SamplingVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame")`

: estimates the sampling variance. See`"SamplingVariance"`

for more details.- estimate
`signature(statistic = "SpatialCumulativeDistributionFunction", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame")`

: estimates the spatial cumulative distribution function (SCDF). See`"SpatialCumulativeDistributionFunction"`

for more details.- estimate
`signature(statistic = "SpatialMean", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame")`

: estimates the spatial mean. See`"SpatialMean"`

for more details.- estimate
`signature(statistic = "SpatialVariance", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame")`

: estimates the spatial variance. See`"SpatialVariance"`

for more details.- estimate
`signature(statistic = "StandardError", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame")`

: estimates the standard error of the spatial mean. See`"StandardError"`

for more details.- estimate
`signature(statistic = "character", stratification = "CompactStratification", samplingPattern = "SamplingPatternRandomSamplingUnits", data = "data.frame")`

: estimates`statistic`

, one of`spatial mean`

,`spatial variance`

,`SCDF`

,`sampling variance`

, or`standard error`

.- getArea
`signature(object = "CompactStratification")`

: returns the area of each stratum.- getCentroid
`signature(object = "CompactStratification")`

: returns the center of gravity of each stratum.- getNumberOfStrata
`signature(object = "CompactStratification")`

: returns the number of strata.- getObjectiveFunctionValue
`signature(object = "CompactStratification")`

: extracts the mean squared shortest distance.- getRelativeArea
`signature(object = "CompactStratification")`

: returns the relative area of each stratum. The sum of the relative areas equals one.- plot
`signature(x = "CompactStratification", y = "missing")`

: plots stratification`x`

.- plot
`signature(x = "CompactStratification", y = "SamplingPattern")`

: plots sampling pattern`y`

on top of stratification`x`

.- plot
`signature(x = "CompactStratification", y = "SamplingPatternPriorPoints")`

: plots sampling pattern`y`

on top of stratification`x`

.- plot
`signature(x = "CompactStratification", y = "SamplingPatternRandomComposite")`

: plots sampling pattern`y`

on top of stratification`x`

.- spsample
`signature(x = "CompactStratification", n = "missing", type = "missing")`

: returns the centers of gravity of each stratum.- spsample
`signature(x = "CompactStratification", n = "numeric", type = "missing")`

: randomly selects`n`

sampling points in each stratum.

Dennis J. J. Walvoort dennis.walvoort@wur.nl, D.J. Brus, J.J. de Gruijter

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