lmBuffer: Linear models from a random sample

In adalardo/lmBuffer: Linear models from a random sample without buffer overlap

Description

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

Usage

lmBuffer(respData, distData, respName, predName, plotVar, rBuff = 1000,
  nSample = 50, maxRand = 10, minRand = 4)

Arguments

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

Details

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

Value

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

Author(s)

Alexandre Adalardo de Oliveira [e-mail]

Melina Oliveira Melito [e-mail] Create a list from a matrix index

Examples

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)

adalardo/lmBuffer documentation built on May 10, 2019, 5:13 a.m.