Description Usage Arguments Details Value Author(s) Examples
Linear models from a random sample
A R package for sample randomization and to build linear models for buffers with different radii, but excluding overlap between observations
1 2 | lmBuffer(respData, distData, respName, predName, plotVar, rBuff = 1000,
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 |
Radius size of buffer. Single integer |
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 |
Package: | lmBuffer |
Version: | 0.01 |
Date: | 2016-06-01 |
Licence: | GPL (>=2) |
Using a vector of buffer radii to random sample observations without overlap at the buffer size
Return a data frame with slope
and r-squared
for each sample draw
Alexandre Adalardo de Oliveira aleadalardo@gmail.com
Melina Oliveira Melito melinamelito@gmail.com Create a list from a matrix index
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | data(respData)
data(distData)
#' respName <- c("sum.biom", "mean.biom", "prop.pion", "density")
plotVar <- "parcela"
predName <- "forest"
rBuff = 1000
applyBuff(respData, distData=distData, respName, predName, plotVar, rBuff = rBuff, nSample = 5, maxRand = 10, minRand = 4)
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 = seq(100, 1500, by=100), nSample = 5, maxRand = 10, minRand = 4)
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