spatialEco (version 0.1-5)

stratified.random: Stratified random sample

Description

Creates a stratified random sample of an sp class object

Usage

stratified.random(x, strata, n = 10, reps = 1, replace = TRUE)

Arguments

x

sp class SpatialDataFrame object (point, polygon, line, pixel)

strata

Column in @data slot with stratification factor

n

Number of random samples

reps

Number of replicates per strata

replace

Sampling with replacement (TRUE|FALSE)

Value

sp SpatialDataFrame object (same as input feature) containing random samples

References

Hudak, A.T., N.L. Crookston, J.S. Evans, M.J. Falkowski, A.M.S. Smith, P. Gessler and P. Morgan. (2006) Regression modelling and mapping of coniferous forest basal area and tree density from discrete-return lidar and multispectral satellite data. Canadian Journal of Remote Sensing 32: 126-138.

Examples

require(sp)
  data(meuse)
    coordinates(meuse) <- ~x+y

# Create stratified variable using quartile breaks
x1 <- cut(meuse@data[,'cadmium'], summary(meuse@data[,'cadmium'])[-4], include.lowest=TRUE)
  levels(x1) <- seq(1,nlevels(x1),1)
x2 <- cut(meuse@data[,'lead'], summary(meuse@data[,'lead'])[-4], include.lowest=TRUE)
  levels(x2) <- seq(1,nlevels(x2),1) 
meuse@data <- cbind(meuse@data, STRAT=paste(x1, x2, sep='.') ) 
   
# 2 replicates and replacement
ssample <- stratified.random(meuse, strata='STRAT', n=2, reps=2)

# 2 replicates and no replacement
ssample.nr <- stratified.random(meuse, strata='STRAT', n=2, reps=2, replace=FALSE)

# n=1 and reps=10 for sequential numbering of samples 
ssample.ct <- stratified.random(meuse, strata='STRAT', n=1, reps=10, replace=TRUE)

# Counts for each full strata (note; 2 strata have only 1 observsation)
tapply(meuse@data$STRAT, meuse@data$STRAT, length)

# Counts for each sampled strata, with replacement
tapply(ssample@data$STRAT, ssample@data$STRAT, length)

# Counts for each sampled strata, without replacement
tapply(ssample.nr@data$STRAT, ssample.nr@data$STRAT, length)

# Counts for each sampled strata, without replacement
tapply(ssample.ct@data$STRAT, ssample.ct@data$STRAT, length)

# Plot random samples colored by replacement
ssample@data$REP <- factor(ssample@data$REP)
  spplot(ssample, 'REP', col.regions=c('red','blue'))