applyBuff: Vectorized function to run lmBuffer on a vector of buffers...
In adalardo/lmBuffer: Linear models from a random sample without buffer overlap

Description Usage Arguments Value Examples

Vectorized function to run lmBuffer on a vector of buffers radii

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applyBuff(respData, distData = distData, respName, predName, plotVar,
  rBuff = seq(100, 1500, by = 100), nSample = 50, maxRand = 10,
  minRand = 4)

`respData`	Data frame with the reponse variables
`distData`	A distance data matrix from samples in respData
`respName`	A vector of names (characters) of the respose variables in respData. Only those are used to generate the linear models
`predName`	Name of the predict variable present in respData
`plotVar`	Column name with plot code in respData
`rBuff`	Vector of radiis of buffer
`nSample`	Number of random samples to draw
`maxRand`	Maximum number of plot in each random sample
`minRand`	Minimum number of plot in each random sample

Return a data frame with slope and r-squared for each sample draw

data(respData)
data(distData)
respName <- c("sum.biom", "mean.biom", "prop.pion", "density")
plotVar <- "parcela"
predName <- "forest"
rBuff <- seq(100, 1500, by=100)
applyBuff(respData, distData=distData, respName, predName, plotVar, rBuff = rBuff, nSample = 5, maxRand = 10, minRand = 4)