CompactStratification-class: Class "CompactStratification"

Description Objects from the Class Slots Extends Methods Author(s)

Description

A class for storing a stratification with compact strata.

Objects from the Class

Objects can be created by calls of the form new("CompactStratification", cells, stratumId, centroids, mssd). However, objects are usually created by calling stratify.

Slots

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.

Extends

Class "Stratification", directly.

Methods

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.

Author(s)

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


spcosa documentation built on May 29, 2017, 10:16 p.m.