revdep/checks.noindex/ecospat/old/ecospat.Rcheck/ecospat-Ex.R
In gbm-developers/gbm: Generalized Boosted Regression Models
pkgname <- "ecospat"
source(file.path(R.home("share"), "R", "examples-header.R"))
options(warn = 1)
library('ecospat')
base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
cleanEx()
nameEx("ecospat.CCV.communityEvaluation.bin")
### * ecospat.CCV.communityEvaluation.bin
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.communityEvaluation.bin
### Title: Calculates a range of community evaluation metrics based on
### different thresholding techniques.
### Aliases: ecospat.CCV.communityEvaluation.bin
### ** Examples
cleanEx()
nameEx("ecospat.CCV.communityEvaluation.prob")
### * ecospat.CCV.communityEvaluation.prob
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.communityEvaluation.prob
### Title: Evaluates community predictions directly on the probabilities
### (i.e., threshold independent)
### Aliases: ecospat.CCV.communityEvaluation.prob
### ** Examples
cleanEx()
nameEx("ecospat.CCV.createDataSplitTable")
### * ecospat.CCV.createDataSplitTable
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.createDataSplitTable
### Title: Creates a DataSplitTable for usage in ecospat.ccv.modeling.
### Aliases: ecospat.CCV.createDataSplitTable
### ** Examples
cleanEx()
nameEx("ecospat.CCV.modeling")
### * ecospat.CCV.modeling
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.modeling
### Title: Runs indivudual species distribuion models with SDMs or ESMs
### Aliases: ecospat.CCV.modeling
### ** Examples
cleanEx()
nameEx("ecospat.CommunityEval")
### * ecospat.CommunityEval
flush(stderr()); flush(stdout())
### Name: ecospat.CommunityEval
### Title: Community Evaluation
### Aliases: ecospat.CommunityEval
### ** Examples
cleanEx()
nameEx("ecospat.Cscore")
### * ecospat.Cscore
flush(stderr()); flush(stdout())
### Name: ecospat.Cscore
### Title: Pairwise co-occurrence Analysis with calculation of the C-score
### index.
### Aliases: ecospat.Cscore
### ** Examples
## Not run:
##D data<- ecospat.testData[c(53,62,58,70,61,66,65,71,69,43,63,56,68,57,55,60,54,67,59,64)]
##D nperm <- 10000
##D outpath <- getwd()
##D Cscore<-ecospat.Cscore(data, nperm, outpath)
##D
## End(Not run)
cleanEx()
nameEx("ecospat.ESM.EnsembleModeling")
### * ecospat.ESM.EnsembleModeling
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.EnsembleModeling
### Title: Ensamble of Small Models: Evaluates and Averages Simple
### Bivariate Models To ESMs
### Aliases: ecospat.ESM.EnsembleModeling
### ** Examples
cleanEx()
nameEx("ecospat.ESM.EnsembleProjection")
### * ecospat.ESM.EnsembleProjection
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.EnsembleProjection
### Title: Ensamble of Small Models: Projects Calibrated ESMs Into New
### Space Or Time.
### Aliases: ecospat.ESM.EnsembleProjection
### ** Examples
cleanEx()
nameEx("ecospat.ESM.Modeling")
### * ecospat.ESM.Modeling
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.Modeling
### Title: Ensamble of Small Models: Calibration of Simple Bivariate Models
### Aliases: ecospat.ESM.Modeling
### ** Examples
cleanEx()
nameEx("ecospat.ESM.Projection")
### * ecospat.ESM.Projection
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.Projection
### Title: Ensamble of Small Models: Projects Simple Bivariate Models Into
### New Space Or Time
### Aliases: ecospat.ESM.Projection
### ** Examples
cleanEx()
nameEx("ecospat.ESM.VarContrib")
### * ecospat.ESM.VarContrib
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.VarContrib
### Title: Variable contribution in ESM
### Aliases: ecospat.ESM.VarContrib
### ** Examples
cleanEx()
nameEx("ecospat.ESM.responsePlot")
### * ecospat.ESM.responsePlot
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.responsePlot
### Title: Produce response plots for ESMs
### Aliases: ecospat.ESM.responsePlot
### ** Examples
cleanEx()
nameEx("ecospat.ESM.threshold")
### * ecospat.ESM.threshold
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.threshold
### Title: Thresholds for Ensamble of Small Models
### Aliases: ecospat.ESM.threshold
### ** Examples
cleanEx()
nameEx("ecospat.Epred")
### * ecospat.Epred
flush(stderr()); flush(stdout())
### Name: ecospat.Epred
### Title: Prediction Mean
### Aliases: ecospat.Epred
### ** Examples
x <- ecospat.testData[c(92,96)]
mean <- ecospat.Epred (x, w=rep(1,ncol(x)), th=0.5)
cleanEx()
nameEx("ecospat.SESAM.prr")
### * ecospat.SESAM.prr
flush(stderr()); flush(stdout())
### Name: ecospat.SESAM.prr
### Title: SESAM Probability Ranking Rule
### Aliases: ecospat.SESAM.prr
### ** Examples
proba <- ecospat.testData[,73:92]
sr <- as.data.frame(rowSums(proba))
ppr<-ecospat.SESAM.prr(proba, sr)
head(ppr)
cleanEx()
nameEx("ecospat.adj.D2")
### * ecospat.adj.D2
flush(stderr()); flush(stdout())
### Name: ecospat.adj.D2.glm
### Title: Calculate An Adjusted D2
### Aliases: ecospat.adj.D2.glm
### ** Examples
data(ecospat.testData)
glm.obj<-glm(Achillea_millefolium~ddeg+mind+srad+slp+topo,
family = binomial, data=ecospat.testData)
ecospat.adj.D2.glm(glm.obj)
cleanEx()
nameEx("ecospat.binary.model")
### * ecospat.binary.model
flush(stderr()); flush(stdout())
### Name: ecospat.binary.model
### Title: Generate Binary Models
### Aliases: ecospat.binary.model
### ** Examples
cleanEx()
nameEx("ecospat.boyce")
### * ecospat.boyce
flush(stderr()); flush(stdout())
### Name: ecospat.boyce
### Title: Calculate Boyce Index
### Aliases: ecospat.boyce
### ** Examples
obs <- (ecospat.testData$glm_Saxifraga_oppositifolia
[which(ecospat.testData$Saxifraga_oppositifolia==1)])
ecospat.boyce (fit = ecospat.testData$glm_Saxifraga_oppositifolia , obs, nclass=0,
window.w="default", res=100, PEplot = TRUE)
cleanEx()
nameEx("ecospat.calculate.pd")
### * ecospat.calculate.pd
flush(stderr()); flush(stdout())
### Name: ecospat.calculate.pd
### Title: Calculate Phylogenetic Diversity Measures
### Aliases: ecospat.calculate.pd
### ** Examples
fpath <- system.file("extdata", "ecospat.testTree.tre", package="ecospat")
tree <-read.tree(fpath)
data <- ecospat.testData[9:52]
pd <- ecospat.calculate.pd(tree, data, method = "spanning", type = "species", root = FALSE,
average = FALSE, verbose = TRUE )
plot(pd)
cleanEx()
nameEx("ecospat.caleval")
### * ecospat.caleval
flush(stderr()); flush(stdout())
### Name: ecospat.caleval
### Title: Calibration And Evaluation Dataset
### Aliases: ecospat.caleval
### ** Examples
data <- ecospat.testData
caleval <- ecospat.caleval (data = ecospat.testData[53], xy = data[2:3], row.num = 1:nrow(data),
nrep = 2, ratio = 0.7, disaggregate = 0.2, pseudoabs = 100, npres = 10, replace = FALSE)
caleval
cleanEx()
nameEx("ecospat.climan")
### * ecospat.climan
flush(stderr()); flush(stdout())
### Name: ecospat.climan
### Title: A climate analogy setection tool for the modeling of species
### distributions
### Aliases: ecospat.climan
### ** Examples
x <- ecospat.testData[c(4:8)]
p<- x[1:90,] #A projection dataset.
ref<- x[91:300,] #A reference dataset
ecospat.climan(ref,p)
cleanEx()
nameEx("ecospat.co_occurrences")
### * ecospat.co_occurrences
flush(stderr()); flush(stdout())
### Name: ecospat.co_occurrences
### Title: Species Co-Occurrences
### Aliases: ecospat.co_occurrences
### ** Examples
cleanEx()
nameEx("ecospat.cohen.kappa")
### * ecospat.cohen.kappa
flush(stderr()); flush(stdout())
### Name: ecospat.cohen.kappa
### Title: Cohen's Kappa
### Aliases: ecospat.cohen.kappa
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
th <- 0.39 # threshold
xtab <- table(Pred >= th, Sp.occ)
ecospat.cohen.kappa(xtab)
cleanEx()
nameEx("ecospat.cons_Cscore")
### * ecospat.cons_Cscore
flush(stderr()); flush(stdout())
### Name: ecospat.cons_Cscore
### Title: Constrained Co-Occurrence Analysis.
### Aliases: ecospat.cons_Cscore
### ** Examples
cleanEx()
nameEx("ecospat.cor.plot")
### * ecospat.cor.plot
flush(stderr()); flush(stdout())
### Name: ecospat.cor.plot
### Title: Correlation Plot
### Aliases: ecospat.cor.plot
### ** Examples
data <- ecospat.testData[,4:8]
ecospat.cor.plot(data)
cleanEx()
nameEx("ecospat.cv.gbm")
### * ecospat.cv.gbm
flush(stderr()); flush(stdout())
### Name: ecospat.cv.gbm
### Title: GBM Cross Validation
### Aliases: ecospat.cv.gbm
### ** Examples
data('ecospat.testData')
# data for Soldanella alpina
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
# gbm model for Soldanella alpina
gbm.Solalp <- gbm(Soldanella_alpina ~ ., data = data.Solalp,
distribution = "bernoulli", cv.folds = 10, n.cores=2)
# cross-validated predictions
gbm.pred <- ecospat.cv.gbm (gbm.obj= gbm.Solalp,data.Solalp,
K=10, cv.lim=10, jack.knife=FALSE)
cleanEx()
nameEx("ecospat.cv.glm")
### * ecospat.cv.glm
flush(stderr()); flush(stdout())
### Name: ecospat.cv.glm
### Title: GLM Cross Validation
### Aliases: ecospat.cv.glm
### ** Examples
cleanEx()
nameEx("ecospat.cv.me")
### * ecospat.cv.me
flush(stderr()); flush(stdout())
### Name: ecospat.cv.me
### Title: Maxent Cross Validation
### Aliases: ecospat.cv.me
### ** Examples
cleanEx()
nameEx("ecospat.cv.rf")
### * ecospat.cv.rf
flush(stderr()); flush(stdout())
### Name: ecospat.cv.rf
### Title: RandomForest Cross Validation
### Aliases: ecospat.cv.rf
### ** Examples
data('ecospat.testData')
# data for Soldanella alpina
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
library(randomForest)
rf.Solalp <- randomForest(x = data.Solalp[,-1], y = as.factor(data.Solalp[,1]))
rf.pred <- ecospat.cv.rf(rf.Solalp, data.Solalp, K = 10, cv.lim = 10,
jack.knife = FALSE, verbose = FALSE)
cleanEx()
nameEx("ecospat.grid.clim.dyn")
### * ecospat.grid.clim.dyn
flush(stderr()); flush(stdout())
### Name: ecospat.grid.clim.dyn
### Title: Dynamic Occurrence Densities Grid
### Aliases: ecospat.grid.clim.dyn
### ** Examples
cleanEx()
nameEx("ecospat.makeDataFrame")
### * ecospat.makeDataFrame
flush(stderr()); flush(stdout())
### Name: ecospat.makeDataFrame
### Title: Make Data Frame
### Aliases: ecospat.makeDataFrame
### ** Examples
cleanEx()
nameEx("ecospat.mantel.correlogram")
### * ecospat.mantel.correlogram
flush(stderr()); flush(stdout())
### Name: ecospat.mantel.correlogram
### Title: Mantel Correlogram
### Aliases: ecospat.mantel.correlogram
### ** Examples
ecospat.mantel.correlogram(dfvar=ecospat.testData[c(2:16)],colxy=1:2, n=100, colvar=3:7,
max=1000, nclass=10, nperm=100)
cleanEx()
nameEx("ecospat.max.kappa")
### * ecospat.max.kappa
flush(stderr()); flush(stdout())
### Name: ecospat.max.kappa
### Title: Maximum Kappa
### Aliases: ecospat.max.kappa
### ** Examples
cleanEx()
nameEx("ecospat.max.tss")
### * ecospat.max.tss
flush(stderr()); flush(stdout())
### Name: ecospat.max.tss
### Title: Maximum TSS
### Aliases: ecospat.max.tss
### Keywords: file
### ** Examples
data(ecospat.testData)
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
TSS100 <- ecospat.max.tss(Pred, Sp.occ)
cleanEx()
nameEx("ecospat.maxentvarimport")
### * ecospat.maxentvarimport
flush(stderr()); flush(stdout())
### Name: ecospat.maxentvarimport
### Title: Maxent Variable Importance
### Aliases: ecospat.maxentvarimport
### ** Examples
library(dismo)
data('ecospat.testData')
# data for Soldanella alpina
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
# copy maxent.jar file in the right folder
path.from<-system.file("extdata", "maxent.txt", package="ecospat")
path.to <- paste0(system.file(package="dismo"), "/java/maxent.txt")
path.to.renamed <- paste0(system.file(package="dismo"), "/java/maxent.jar")
file.copy(path.from,path.to,overwrite = TRUE)
file.rename(path.to, path.to.renamed)
if (file.exists(path.to.renamed) & require(rJava)) {
me <- maxent(data.Solalp[,-1],data.Solalp[,1])
ecospat.maxentvarimport (model=me, dfvar=data.Solalp[,-1], nperm=5)
}
cleanEx()
nameEx("ecospat.mdr")
### * ecospat.mdr
flush(stderr()); flush(stdout())
### Name: ecospat.mdr
### Title: Minimum Dispersal Routes)
### Aliases: ecospat.mdr
### ** Examples
library(maps)
data(ecospat.testMdr)
data<- ecospat.testMdr
intros<-order(data$date)[1:2] # rows corresponding to first introductions
# plot observed situation
plot(data[,2:1],pch=15,cex=0.5)
points(data[intros,2:1],pch=19,col="red")
text(data[,2]+0.5,data[,1]+0.5,data[,3],cex=0.5)
map(add=TRUE)
# calculate minimum cost arborescence (MCA) of dispersal routes
obs<-ecospat.mdr(data=data,xcol=2,ycol=1,datecol=3,mode="min",rep=100,
mean.date.error=1,fixed.sources.rows=intros)
# plot MCA results
# arrows' thickness indicate support for the routes
mca<-obs[[1]]
plot(mca[,3:4],type="n",xlab="longitude",ylab="latitude")
arrows(mca[,1],mca[,2],mca[,3],mca[,4],length = 0.05,lwd=mca$bootstrap.value*2)
map(add=TRUE)
# plot intros
points(data[intros,2:1],pch=19,col="red")
text(data[intros,2]+0.5,data[intros,1]+0.5,data[intros,3],cex=1,col="red")
# dispersal routes statistics
obs[[2]] # total routes length in DD
obs[[3]] # median dispersal rate in DD/yr
obs[[4]] # number of outcoming nodes
cleanEx()
nameEx("ecospat.mess")
### * ecospat.mess
flush(stderr()); flush(stdout())
### Name: ecospat.mess
### Title: MESS
### Aliases: ecospat.mess
### ** Examples
x <- ecospat.testData[c(2,3,4:8)]
proj <- x[1:90,] #A projection dataset.
cal <- x[91:300,] #A calibration dataset
#Create a MESS object
mess.object <- ecospat.mess (proj, cal, w="default")
#Plot MESS
ecospat.plot.mess (mess.object, cex=1, pch=15)
cleanEx()
nameEx("ecospat.meva.table")
### * ecospat.meva.table
flush(stderr()); flush(stdout())
### Name: ecospat.meva.table
### Title: Model Evaluation For A Given Threshold Value
### Aliases: ecospat.meva.table
### Keywords: file
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
meva <- ecospat.meva.table (Pred, Sp.occ, 0.39)
cleanEx()
nameEx("ecospat.mpa")
### * ecospat.mpa
flush(stderr()); flush(stdout())
### Name: ecospat.mpa
### Title: Minimal Predicted Area
### Aliases: ecospat.mpa
### ** Examples
data(ecospat.testData)
obs <- (ecospat.testData$glm_Saxifraga_oppositifolia
[which(ecospat.testData$Saxifraga_oppositifolia==1)])
ecospat.mpa(obs)
ecospat.mpa(obs,perc=1) ## 100 percent of the presences encompassed
cleanEx()
nameEx("ecospat.niche.dynIndexProjGeo")
### * ecospat.niche.dynIndexProjGeo
flush(stderr()); flush(stdout())
### Name: ecospat.niche.dynIndexProjGeo
### Title: Projection of niche dynamic indices to the Geography
### Aliases: ecospat.niche.dynIndexProjGeo
### ** Examples
cleanEx()
nameEx("ecospat.niche.zProjGeo")
### * ecospat.niche.zProjGeo
flush(stderr()); flush(stdout())
### Name: ecospat.niche.zProjGeo
### Title: Projection of Occurrence Densities to the Geography
### Aliases: ecospat.niche.zProjGeo
### ** Examples
cleanEx()
nameEx("ecospat.npred")
### * ecospat.npred
flush(stderr()); flush(stdout())
### Name: ecospat.npred
### Title: Number Of Predictors
### Aliases: ecospat.npred
### ** Examples
colvar <- ecospat.testData[c(4:8)]
x <- cor(colvar, method="pearson")
ecospat.npred (x, th=0.75)
cleanEx()
nameEx("ecospat.occ.desaggregation")
### * ecospat.occ.desaggregation
flush(stderr()); flush(stdout())
### Name: ecospat.occ.desaggregation
### Title: Species Occurrences Desaggregation
### Aliases: ecospat.occ.desaggregation
### ** Examples
cleanEx()
nameEx("ecospat.occupied.patch")
### * ecospat.occupied.patch
flush(stderr()); flush(stdout())
### Name: ecospat.occupied.patch
### Title: Extract occupied patches of a species in geographic space.)
### Aliases: ecospat.occupied.patch
### Keywords: file
### ** Examples
cleanEx()
nameEx("ecospat.permut.glm")
### * ecospat.permut.glm
flush(stderr()); flush(stdout())
### Name: ecospat.permut.glm
### Title: GLM Permutation Function
### Aliases: ecospat.permut.glm
### ** Examples
cleanEx()
nameEx("ecospat.plot.kappa")
### * ecospat.plot.kappa
flush(stderr()); flush(stdout())
### Name: ecospat.plot.kappa
### Title: Plot Kappa
### Aliases: ecospat.plot.kappa
### Keywords: file
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
ecospat.plot.kappa(Pred, Sp.occ)
cleanEx()
nameEx("ecospat.plot.mess")
### * ecospat.plot.mess
flush(stderr()); flush(stdout())
### Name: ecospat.plot.mess
### Title: Plot MESS
### Aliases: ecospat.plot.mess
### ** Examples
cleanEx()
nameEx("ecospat.plot.tss")
### * ecospat.plot.tss
flush(stderr()); flush(stdout())
### Name: ecospat.plot.tss
### Title: Plot True skill statistic (TSS)
### Aliases: ecospat.plot.tss
### Keywords: file
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
ecospat.plot.tss(Pred, Sp.occ)
cleanEx()
nameEx("ecospat.rand.pseudoabsences")
### * ecospat.rand.pseudoabsences
flush(stderr()); flush(stdout())
### Name: ecospat.rand.pseudoabsences
### Title: Sample Pseudo-Absences
### Aliases: ecospat.rand.pseudoabsences
### ** Examples
glob <- ecospat.testData[2:8]
presence <- ecospat.testData[c(2:3,9)]
presence <- presence[presence[,3]==1,1:2]
ecospat.rand.pseudoabsences (nbabsences=10, glob=glob, colxyglob=1:2, colvar = "all",
presence= presence, colxypresence=1:2, mindist=20)
cleanEx()
nameEx("ecospat.rangesize")
### * ecospat.rangesize
flush(stderr()); flush(stdout())
### Name: ecospat.rangesize
### Title: Quantification of the range size of a species using habitat
### suitability maps and IUCN criteria)
### Aliases: ecospat.rangesize
### Keywords: file
### ** Examples
cleanEx()
nameEx("ecospat.rcls.grd")
### * ecospat.rcls.grd
flush(stderr()); flush(stdout())
### Name: ecospat.rcls.grd
### Title: Reclassifying grids function
### Aliases: ecospat.rcls.grd
### ** Examples
library(raster)
library(classInt)
bio3<- raster(system.file("external/bioclim/current/bio3.grd",package="biomod2"))
bio12<- raster(system.file("external/bioclim/current/bio12.grd",package="biomod2"))
B3.rcl<-ecospat.rcls.grd(bio3,9)
B12.rcl<-ecospat.rcls.grd(bio12,9)
B3B12.comb <- B12.rcl+B3.rcl*10
# Plotting a histogram of the classes
hist(B3B12.comb,breaks=100,col=heat.colors(88))
# Plotting the new RasterLayer (9x9 classes)
plot(B3B12.comb,col=rev(rainbow(88)),main="Stratified map")
cleanEx()
nameEx("ecospat.recstrat_prop")
### * ecospat.recstrat_prop
flush(stderr()); flush(stdout())
### Name: ecospat.recstrat_prop
### Title: Random Ecologically Stratified Sampling of propotional numbers
### Aliases: ecospat.recstrat_prop
### ** Examples
library(raster)
library(classInt)
bio3<- raster(system.file("external/bioclim/current/bio3.grd",package="biomod2"))
bio12<- raster(system.file("external/bioclim/current/bio12.grd",package="biomod2"))
B3.rcl<-ecospat.rcls.grd(bio3,9)
B12.rcl<-ecospat.rcls.grd(bio12,9)
B3B12.comb <- B12.rcl+B3.rcl*10
B3B12.prop_samples <- ecospat.recstrat_prop(B3B12.comb,100)
plot(B3B12.comb)
points(B3B12.prop_samples$x,B3B12.prop_samples$y,pch=16,cex=0.6,col=B3B12.prop_samples$class)
cleanEx()
nameEx("ecospat.recstrat_regl")
### * ecospat.recstrat_regl
flush(stderr()); flush(stdout())
### Name: ecospat.recstrat_regl
### Title: Random Ecologically Stratified Sampling of equal numbers
### Aliases: ecospat.recstrat_regl
### ** Examples
library(raster)
library(classInt)
bio3<- raster(system.file("external/bioclim/current/bio3.grd",package="biomod2"))
bio12<- raster(system.file("external/bioclim/current/bio12.grd",package="biomod2"))
B3.rcl<-ecospat.rcls.grd(bio3,9)
B12.rcl<-ecospat.rcls.grd(bio12,9)
B3B12.comb <- B12.rcl+B3.rcl*10
B3B12.regl_samples <- ecospat.recstrat_prop(B3B12.comb,100)
plot(B3B12.comb)
points(B3B12.regl_samples$x,B3B12.regl_samples$y,pch=16,cex=0.6,col=B3B12.regl_samples$class)
cleanEx()
nameEx("ecospat.sample.envar")
### * ecospat.sample.envar
flush(stderr()); flush(stdout())
### Name: ecospat.sample.envar
### Title: Sample Environmental Variables
### Aliases: ecospat.sample.envar
### ** Examples
cleanEx()
nameEx("ecospat.testData")
### * ecospat.testData
flush(stderr()); flush(stdout())
### Name: ecospat.testData
### Title: Test Data For The Ecospat package
### Aliases: ecospat.testData
### ** Examples
data(ecospat.testData)
str(ecospat.testData)
dim(ecospat.testData)
names(ecospat.testData)
cleanEx()
nameEx("ecospat.testEnvRaster")
### * ecospat.testEnvRaster
flush(stderr()); flush(stdout())
### Name: ecospat.testEnvRaster
### Title: Test Environmental Rasters for The Ecospat package
### Aliases: ecospat.testEnvRaster
### ** Examples
## Not run:
##D fpath <- system.file("extdata", "ecospat.testEnvRaster.RData", package="ecospat")
##D load(fpath)
##D plot(env)
## End(Not run)
cleanEx()
nameEx("ecospat.testMdr")
### * ecospat.testMdr
flush(stderr()); flush(stdout())
### Name: ecospat.testMdr
### Title: Test Data For The ecospat.mdr function
### Aliases: ecospat.testMdr
### ** Examples
data(ecospat.testMdr)
str(ecospat.testMdr)
dim(ecospat.testMdr)
cleanEx()
nameEx("ecospat.testNiche")
### * ecospat.testNiche
flush(stderr()); flush(stdout())
### Name: ecospat.testNiche
### Title: Test Data For The Niche Overlap Analysis
### Aliases: ecospat.testNiche
### ** Examples
data(ecospat.testNiche)
dim(ecospat.testNiche)
names(ecospat.testNiche)
cleanEx()
nameEx("ecospat.testNiche.inv")
### * ecospat.testNiche.inv
flush(stderr()); flush(stdout())
### Name: ecospat.testNiche.inv
### Title: Test Data For The Niche Dynamics Analysis In The Invaded Range
### Of A Hypothetical Species
### Aliases: ecospat.testNiche.inv
### ** Examples
data(ecospat.testNiche.inv)
str(ecospat.testNiche.inv)
dim(ecospat.testNiche.inv)
names(ecospat.testNiche.inv)
cleanEx()
nameEx("ecospat.testNiche.nat")
### * ecospat.testNiche.nat
flush(stderr()); flush(stdout())
### Name: ecospat.testNiche.nat
### Title: Test Data For The Niche Dynamics Analysis In The Native Range Of
### A Hypothetical Species
### Aliases: ecospat.testNiche.nat
### ** Examples
data(ecospat.testNiche.nat)
str(ecospat.testNiche.nat)
dim(ecospat.testNiche.nat)
names(ecospat.testNiche.nat)
cleanEx()
nameEx("ecospat.testTree")
### * ecospat.testTree
flush(stderr()); flush(stdout())
### Name: ecospat.testTree
### Title: Test Tree For The Ecospat package
### Aliases: ecospat.testTree
### ** Examples
fpath <- system.file("extdata", "ecospat.testTree.tre", package="ecospat")
tree <- read.tree(fpath)
plot(tree)
cleanEx()
nameEx("ecospat.varpart")
### * ecospat.varpart
flush(stderr()); flush(stdout())
### Name: ecospat.varpart
### Title: Variation Partitioning For GLM Or GAM
### Aliases: ecospat.varpart
### ** Examples
library(rms)
data('ecospat.testData')
# data for Soldanella alpina and Achillea millefolium
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
# glm models for Soldanella alpina
glm.Solalp1 <- glm("Soldanella_alpina ~ pol(ddeg,2) + pol(mind,2) + pol(srad,2)",
data = data.Solalp, family = binomial)
glm.Solalp2 <- glm("Soldanella_alpina ~ pol(slp,2) + pol(topo,2)",
data = data.Solalp, family = binomial)
ecospat.varpart (model.1= glm.Solalp1, model.2= glm.Solalp2, model.12= glm.Solalp2)
### * <FOOTER>
###
cleanEx()
options(digits = 7L)
base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
grDevices::dev.off()
###
### Local variables: ***
### mode: outline-minor ***
### outline-regexp: "\\(> \\)?### [*]+" ***
### End: ***
quit('no')
gbm-developers/gbm documentation built on Feb. 16, 2024, 6:13 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
pkgname <- "ecospat"
source(file.path(R.home("share"), "R", "examples-header.R"))
options(warn = 1)
library('ecospat')
base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
cleanEx()
nameEx("ecospat.CCV.communityEvaluation.bin")
### * ecospat.CCV.communityEvaluation.bin
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.communityEvaluation.bin
### Title: Calculates a range of community evaluation metrics based on
### different thresholding techniques.
### Aliases: ecospat.CCV.communityEvaluation.bin
### ** Examples
cleanEx()
nameEx("ecospat.CCV.communityEvaluation.prob")
### * ecospat.CCV.communityEvaluation.prob
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.communityEvaluation.prob
### Title: Evaluates community predictions directly on the probabilities
### (i.e., threshold independent)
### Aliases: ecospat.CCV.communityEvaluation.prob
### ** Examples
cleanEx()
nameEx("ecospat.CCV.createDataSplitTable")
### * ecospat.CCV.createDataSplitTable
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.createDataSplitTable
### Title: Creates a DataSplitTable for usage in ecospat.ccv.modeling.
### Aliases: ecospat.CCV.createDataSplitTable
### ** Examples
cleanEx()
nameEx("ecospat.CCV.modeling")
### * ecospat.CCV.modeling
flush(stderr()); flush(stdout())
### Name: ecospat.CCV.modeling
### Title: Runs indivudual species distribuion models with SDMs or ESMs
### Aliases: ecospat.CCV.modeling
### ** Examples
cleanEx()
nameEx("ecospat.CommunityEval")
### * ecospat.CommunityEval
flush(stderr()); flush(stdout())
### Name: ecospat.CommunityEval
### Title: Community Evaluation
### Aliases: ecospat.CommunityEval
### ** Examples
cleanEx()
nameEx("ecospat.Cscore")
### * ecospat.Cscore
flush(stderr()); flush(stdout())
### Name: ecospat.Cscore
### Title: Pairwise co-occurrence Analysis with calculation of the C-score
### index.
### Aliases: ecospat.Cscore
### ** Examples
## Not run:
##D data<- ecospat.testData[c(53,62,58,70,61,66,65,71,69,43,63,56,68,57,55,60,54,67,59,64)]
##D nperm <- 10000
##D outpath <- getwd()
##D Cscore<-ecospat.Cscore(data, nperm, outpath)
##D
## End(Not run)
cleanEx()
nameEx("ecospat.ESM.EnsembleModeling")
### * ecospat.ESM.EnsembleModeling
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.EnsembleModeling
### Title: Ensamble of Small Models: Evaluates and Averages Simple
### Bivariate Models To ESMs
### Aliases: ecospat.ESM.EnsembleModeling
### ** Examples
cleanEx()
nameEx("ecospat.ESM.EnsembleProjection")
### * ecospat.ESM.EnsembleProjection
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.EnsembleProjection
### Title: Ensamble of Small Models: Projects Calibrated ESMs Into New
### Space Or Time.
### Aliases: ecospat.ESM.EnsembleProjection
### ** Examples
cleanEx()
nameEx("ecospat.ESM.Modeling")
### * ecospat.ESM.Modeling
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.Modeling
### Title: Ensamble of Small Models: Calibration of Simple Bivariate Models
### Aliases: ecospat.ESM.Modeling
### ** Examples
cleanEx()
nameEx("ecospat.ESM.Projection")
### * ecospat.ESM.Projection
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.Projection
### Title: Ensamble of Small Models: Projects Simple Bivariate Models Into
### New Space Or Time
### Aliases: ecospat.ESM.Projection
### ** Examples
cleanEx()
nameEx("ecospat.ESM.VarContrib")
### * ecospat.ESM.VarContrib
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.VarContrib
### Title: Variable contribution in ESM
### Aliases: ecospat.ESM.VarContrib
### ** Examples
cleanEx()
nameEx("ecospat.ESM.responsePlot")
### * ecospat.ESM.responsePlot
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.responsePlot
### Title: Produce response plots for ESMs
### Aliases: ecospat.ESM.responsePlot
### ** Examples
cleanEx()
nameEx("ecospat.ESM.threshold")
### * ecospat.ESM.threshold
flush(stderr()); flush(stdout())
### Name: ecospat.ESM.threshold
### Title: Thresholds for Ensamble of Small Models
### Aliases: ecospat.ESM.threshold
### ** Examples
cleanEx()
nameEx("ecospat.Epred")
### * ecospat.Epred
flush(stderr()); flush(stdout())
### Name: ecospat.Epred
### Title: Prediction Mean
### Aliases: ecospat.Epred
### ** Examples
x <- ecospat.testData[c(92,96)]
mean <- ecospat.Epred (x, w=rep(1,ncol(x)), th=0.5)
cleanEx()
nameEx("ecospat.SESAM.prr")
### * ecospat.SESAM.prr
flush(stderr()); flush(stdout())
### Name: ecospat.SESAM.prr
### Title: SESAM Probability Ranking Rule
### Aliases: ecospat.SESAM.prr
### ** Examples
proba <- ecospat.testData[,73:92]
sr <- as.data.frame(rowSums(proba))
ppr<-ecospat.SESAM.prr(proba, sr)
head(ppr)
cleanEx()
nameEx("ecospat.adj.D2")
### * ecospat.adj.D2
flush(stderr()); flush(stdout())
### Name: ecospat.adj.D2.glm
### Title: Calculate An Adjusted D2
### Aliases: ecospat.adj.D2.glm
### ** Examples
data(ecospat.testData)
glm.obj<-glm(Achillea_millefolium~ddeg+mind+srad+slp+topo,
family = binomial, data=ecospat.testData)
ecospat.adj.D2.glm(glm.obj)
cleanEx()
nameEx("ecospat.binary.model")
### * ecospat.binary.model
flush(stderr()); flush(stdout())
### Name: ecospat.binary.model
### Title: Generate Binary Models
### Aliases: ecospat.binary.model
### ** Examples
cleanEx()
nameEx("ecospat.boyce")
### * ecospat.boyce
flush(stderr()); flush(stdout())
### Name: ecospat.boyce
### Title: Calculate Boyce Index
### Aliases: ecospat.boyce
### ** Examples
obs <- (ecospat.testData$glm_Saxifraga_oppositifolia
[which(ecospat.testData$Saxifraga_oppositifolia==1)])
ecospat.boyce (fit = ecospat.testData$glm_Saxifraga_oppositifolia , obs, nclass=0,
window.w="default", res=100, PEplot = TRUE)
cleanEx()
nameEx("ecospat.calculate.pd")
### * ecospat.calculate.pd
flush(stderr()); flush(stdout())
### Name: ecospat.calculate.pd
### Title: Calculate Phylogenetic Diversity Measures
### Aliases: ecospat.calculate.pd
### ** Examples
fpath <- system.file("extdata", "ecospat.testTree.tre", package="ecospat")
tree <-read.tree(fpath)
data <- ecospat.testData[9:52]
pd <- ecospat.calculate.pd(tree, data, method = "spanning", type = "species", root = FALSE,
average = FALSE, verbose = TRUE )
plot(pd)
cleanEx()
nameEx("ecospat.caleval")
### * ecospat.caleval
flush(stderr()); flush(stdout())
### Name: ecospat.caleval
### Title: Calibration And Evaluation Dataset
### Aliases: ecospat.caleval
### ** Examples
data <- ecospat.testData
caleval <- ecospat.caleval (data = ecospat.testData[53], xy = data[2:3], row.num = 1:nrow(data),
nrep = 2, ratio = 0.7, disaggregate = 0.2, pseudoabs = 100, npres = 10, replace = FALSE)
caleval
cleanEx()
nameEx("ecospat.climan")
### * ecospat.climan
flush(stderr()); flush(stdout())
### Name: ecospat.climan
### Title: A climate analogy setection tool for the modeling of species
### distributions
### Aliases: ecospat.climan
### ** Examples
x <- ecospat.testData[c(4:8)]
p<- x[1:90,] #A projection dataset.
ref<- x[91:300,] #A reference dataset
ecospat.climan(ref,p)
cleanEx()
nameEx("ecospat.co_occurrences")
### * ecospat.co_occurrences
flush(stderr()); flush(stdout())
### Name: ecospat.co_occurrences
### Title: Species Co-Occurrences
### Aliases: ecospat.co_occurrences
### ** Examples
cleanEx()
nameEx("ecospat.cohen.kappa")
### * ecospat.cohen.kappa
flush(stderr()); flush(stdout())
### Name: ecospat.cohen.kappa
### Title: Cohen's Kappa
### Aliases: ecospat.cohen.kappa
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
th <- 0.39 # threshold
xtab <- table(Pred >= th, Sp.occ)
ecospat.cohen.kappa(xtab)
cleanEx()
nameEx("ecospat.cons_Cscore")
### * ecospat.cons_Cscore
flush(stderr()); flush(stdout())
### Name: ecospat.cons_Cscore
### Title: Constrained Co-Occurrence Analysis.
### Aliases: ecospat.cons_Cscore
### ** Examples
cleanEx()
nameEx("ecospat.cor.plot")
### * ecospat.cor.plot
flush(stderr()); flush(stdout())
### Name: ecospat.cor.plot
### Title: Correlation Plot
### Aliases: ecospat.cor.plot
### ** Examples
data <- ecospat.testData[,4:8]
ecospat.cor.plot(data)
cleanEx()
nameEx("ecospat.cv.gbm")
### * ecospat.cv.gbm
flush(stderr()); flush(stdout())
### Name: ecospat.cv.gbm
### Title: GBM Cross Validation
### Aliases: ecospat.cv.gbm
### ** Examples
data('ecospat.testData')
# data for Soldanella alpina
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
# gbm model for Soldanella alpina
gbm.Solalp <- gbm(Soldanella_alpina ~ ., data = data.Solalp,
distribution = "bernoulli", cv.folds = 10, n.cores=2)
# cross-validated predictions
gbm.pred <- ecospat.cv.gbm (gbm.obj= gbm.Solalp,data.Solalp,
K=10, cv.lim=10, jack.knife=FALSE)
cleanEx()
nameEx("ecospat.cv.glm")
### * ecospat.cv.glm
flush(stderr()); flush(stdout())
### Name: ecospat.cv.glm
### Title: GLM Cross Validation
### Aliases: ecospat.cv.glm
### ** Examples
cleanEx()
nameEx("ecospat.cv.me")
### * ecospat.cv.me
flush(stderr()); flush(stdout())
### Name: ecospat.cv.me
### Title: Maxent Cross Validation
### Aliases: ecospat.cv.me
### ** Examples
cleanEx()
nameEx("ecospat.cv.rf")
### * ecospat.cv.rf
flush(stderr()); flush(stdout())
### Name: ecospat.cv.rf
### Title: RandomForest Cross Validation
### Aliases: ecospat.cv.rf
### ** Examples
data('ecospat.testData')
# data for Soldanella alpina
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
library(randomForest)
rf.Solalp <- randomForest(x = data.Solalp[,-1], y = as.factor(data.Solalp[,1]))
rf.pred <- ecospat.cv.rf(rf.Solalp, data.Solalp, K = 10, cv.lim = 10,
jack.knife = FALSE, verbose = FALSE)
cleanEx()
nameEx("ecospat.grid.clim.dyn")
### * ecospat.grid.clim.dyn
flush(stderr()); flush(stdout())
### Name: ecospat.grid.clim.dyn
### Title: Dynamic Occurrence Densities Grid
### Aliases: ecospat.grid.clim.dyn
### ** Examples
cleanEx()
nameEx("ecospat.makeDataFrame")
### * ecospat.makeDataFrame
flush(stderr()); flush(stdout())
### Name: ecospat.makeDataFrame
### Title: Make Data Frame
### Aliases: ecospat.makeDataFrame
### ** Examples
cleanEx()
nameEx("ecospat.mantel.correlogram")
### * ecospat.mantel.correlogram
flush(stderr()); flush(stdout())
### Name: ecospat.mantel.correlogram
### Title: Mantel Correlogram
### Aliases: ecospat.mantel.correlogram
### ** Examples
ecospat.mantel.correlogram(dfvar=ecospat.testData[c(2:16)],colxy=1:2, n=100, colvar=3:7,
max=1000, nclass=10, nperm=100)
cleanEx()
nameEx("ecospat.max.kappa")
### * ecospat.max.kappa
flush(stderr()); flush(stdout())
### Name: ecospat.max.kappa
### Title: Maximum Kappa
### Aliases: ecospat.max.kappa
### ** Examples
cleanEx()
nameEx("ecospat.max.tss")
### * ecospat.max.tss
flush(stderr()); flush(stdout())
### Name: ecospat.max.tss
### Title: Maximum TSS
### Aliases: ecospat.max.tss
### Keywords: file
### ** Examples
data(ecospat.testData)
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
TSS100 <- ecospat.max.tss(Pred, Sp.occ)
cleanEx()
nameEx("ecospat.maxentvarimport")
### * ecospat.maxentvarimport
flush(stderr()); flush(stdout())
### Name: ecospat.maxentvarimport
### Title: Maxent Variable Importance
### Aliases: ecospat.maxentvarimport
### ** Examples
library(dismo)
data('ecospat.testData')
# data for Soldanella alpina
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
# copy maxent.jar file in the right folder
path.from<-system.file("extdata", "maxent.txt", package="ecospat")
path.to <- paste0(system.file(package="dismo"), "/java/maxent.txt")
path.to.renamed <- paste0(system.file(package="dismo"), "/java/maxent.jar")
file.copy(path.from,path.to,overwrite = TRUE)
file.rename(path.to, path.to.renamed)
if (file.exists(path.to.renamed) & require(rJava)) {
me <- maxent(data.Solalp[,-1],data.Solalp[,1])
ecospat.maxentvarimport (model=me, dfvar=data.Solalp[,-1], nperm=5)
}
cleanEx()
nameEx("ecospat.mdr")
### * ecospat.mdr
flush(stderr()); flush(stdout())
### Name: ecospat.mdr
### Title: Minimum Dispersal Routes)
### Aliases: ecospat.mdr
### ** Examples
library(maps)
data(ecospat.testMdr)
data<- ecospat.testMdr
intros<-order(data$date)[1:2] # rows corresponding to first introductions
# plot observed situation
plot(data[,2:1],pch=15,cex=0.5)
points(data[intros,2:1],pch=19,col="red")
text(data[,2]+0.5,data[,1]+0.5,data[,3],cex=0.5)
map(add=TRUE)
# calculate minimum cost arborescence (MCA) of dispersal routes
obs<-ecospat.mdr(data=data,xcol=2,ycol=1,datecol=3,mode="min",rep=100,
mean.date.error=1,fixed.sources.rows=intros)
# plot MCA results
# arrows' thickness indicate support for the routes
mca<-obs[[1]]
plot(mca[,3:4],type="n",xlab="longitude",ylab="latitude")
arrows(mca[,1],mca[,2],mca[,3],mca[,4],length = 0.05,lwd=mca$bootstrap.value*2)
map(add=TRUE)
# plot intros
points(data[intros,2:1],pch=19,col="red")
text(data[intros,2]+0.5,data[intros,1]+0.5,data[intros,3],cex=1,col="red")
# dispersal routes statistics
obs[[2]] # total routes length in DD
obs[[3]] # median dispersal rate in DD/yr
obs[[4]] # number of outcoming nodes
cleanEx()
nameEx("ecospat.mess")
### * ecospat.mess
flush(stderr()); flush(stdout())
### Name: ecospat.mess
### Title: MESS
### Aliases: ecospat.mess
### ** Examples
x <- ecospat.testData[c(2,3,4:8)]
proj <- x[1:90,] #A projection dataset.
cal <- x[91:300,] #A calibration dataset
#Create a MESS object
mess.object <- ecospat.mess (proj, cal, w="default")
#Plot MESS
ecospat.plot.mess (mess.object, cex=1, pch=15)
cleanEx()
nameEx("ecospat.meva.table")
### * ecospat.meva.table
flush(stderr()); flush(stdout())
### Name: ecospat.meva.table
### Title: Model Evaluation For A Given Threshold Value
### Aliases: ecospat.meva.table
### Keywords: file
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
meva <- ecospat.meva.table (Pred, Sp.occ, 0.39)
cleanEx()
nameEx("ecospat.mpa")
### * ecospat.mpa
flush(stderr()); flush(stdout())
### Name: ecospat.mpa
### Title: Minimal Predicted Area
### Aliases: ecospat.mpa
### ** Examples
data(ecospat.testData)
obs <- (ecospat.testData$glm_Saxifraga_oppositifolia
[which(ecospat.testData$Saxifraga_oppositifolia==1)])
ecospat.mpa(obs)
ecospat.mpa(obs,perc=1) ## 100 percent of the presences encompassed
cleanEx()
nameEx("ecospat.niche.dynIndexProjGeo")
### * ecospat.niche.dynIndexProjGeo
flush(stderr()); flush(stdout())
### Name: ecospat.niche.dynIndexProjGeo
### Title: Projection of niche dynamic indices to the Geography
### Aliases: ecospat.niche.dynIndexProjGeo
### ** Examples
cleanEx()
nameEx("ecospat.niche.zProjGeo")
### * ecospat.niche.zProjGeo
flush(stderr()); flush(stdout())
### Name: ecospat.niche.zProjGeo
### Title: Projection of Occurrence Densities to the Geography
### Aliases: ecospat.niche.zProjGeo
### ** Examples
cleanEx()
nameEx("ecospat.npred")
### * ecospat.npred
flush(stderr()); flush(stdout())
### Name: ecospat.npred
### Title: Number Of Predictors
### Aliases: ecospat.npred
### ** Examples
colvar <- ecospat.testData[c(4:8)]
x <- cor(colvar, method="pearson")
ecospat.npred (x, th=0.75)
cleanEx()
nameEx("ecospat.occ.desaggregation")
### * ecospat.occ.desaggregation
flush(stderr()); flush(stdout())
### Name: ecospat.occ.desaggregation
### Title: Species Occurrences Desaggregation
### Aliases: ecospat.occ.desaggregation
### ** Examples
cleanEx()
nameEx("ecospat.occupied.patch")
### * ecospat.occupied.patch
flush(stderr()); flush(stdout())
### Name: ecospat.occupied.patch
### Title: Extract occupied patches of a species in geographic space.)
### Aliases: ecospat.occupied.patch
### Keywords: file
### ** Examples
cleanEx()
nameEx("ecospat.permut.glm")
### * ecospat.permut.glm
flush(stderr()); flush(stdout())
### Name: ecospat.permut.glm
### Title: GLM Permutation Function
### Aliases: ecospat.permut.glm
### ** Examples
cleanEx()
nameEx("ecospat.plot.kappa")
### * ecospat.plot.kappa
flush(stderr()); flush(stdout())
### Name: ecospat.plot.kappa
### Title: Plot Kappa
### Aliases: ecospat.plot.kappa
### Keywords: file
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
ecospat.plot.kappa(Pred, Sp.occ)
cleanEx()
nameEx("ecospat.plot.mess")
### * ecospat.plot.mess
flush(stderr()); flush(stdout())
### Name: ecospat.plot.mess
### Title: Plot MESS
### Aliases: ecospat.plot.mess
### ** Examples
cleanEx()
nameEx("ecospat.plot.tss")
### * ecospat.plot.tss
flush(stderr()); flush(stdout())
### Name: ecospat.plot.tss
### Title: Plot True skill statistic (TSS)
### Aliases: ecospat.plot.tss
### Keywords: file
### ** Examples
Pred <- ecospat.testData$glm_Agrostis_capillaris
Sp.occ <- ecospat.testData$Agrostis_capillaris
ecospat.plot.tss(Pred, Sp.occ)
cleanEx()
nameEx("ecospat.rand.pseudoabsences")
### * ecospat.rand.pseudoabsences
flush(stderr()); flush(stdout())
### Name: ecospat.rand.pseudoabsences
### Title: Sample Pseudo-Absences
### Aliases: ecospat.rand.pseudoabsences
### ** Examples
glob <- ecospat.testData[2:8]
presence <- ecospat.testData[c(2:3,9)]
presence <- presence[presence[,3]==1,1:2]
ecospat.rand.pseudoabsences (nbabsences=10, glob=glob, colxyglob=1:2, colvar = "all",
presence= presence, colxypresence=1:2, mindist=20)
cleanEx()
nameEx("ecospat.rangesize")
### * ecospat.rangesize
flush(stderr()); flush(stdout())
### Name: ecospat.rangesize
### Title: Quantification of the range size of a species using habitat
### suitability maps and IUCN criteria)
### Aliases: ecospat.rangesize
### Keywords: file
### ** Examples
cleanEx()
nameEx("ecospat.rcls.grd")
### * ecospat.rcls.grd
flush(stderr()); flush(stdout())
### Name: ecospat.rcls.grd
### Title: Reclassifying grids function
### Aliases: ecospat.rcls.grd
### ** Examples
library(raster)
library(classInt)
bio3<- raster(system.file("external/bioclim/current/bio3.grd",package="biomod2"))
bio12<- raster(system.file("external/bioclim/current/bio12.grd",package="biomod2"))
B3.rcl<-ecospat.rcls.grd(bio3,9)
B12.rcl<-ecospat.rcls.grd(bio12,9)
B3B12.comb <- B12.rcl+B3.rcl*10
# Plotting a histogram of the classes
hist(B3B12.comb,breaks=100,col=heat.colors(88))
# Plotting the new RasterLayer (9x9 classes)
plot(B3B12.comb,col=rev(rainbow(88)),main="Stratified map")
cleanEx()
nameEx("ecospat.recstrat_prop")
### * ecospat.recstrat_prop
flush(stderr()); flush(stdout())
### Name: ecospat.recstrat_prop
### Title: Random Ecologically Stratified Sampling of propotional numbers
### Aliases: ecospat.recstrat_prop
### ** Examples
library(raster)
library(classInt)
bio3<- raster(system.file("external/bioclim/current/bio3.grd",package="biomod2"))
bio12<- raster(system.file("external/bioclim/current/bio12.grd",package="biomod2"))
B3.rcl<-ecospat.rcls.grd(bio3,9)
B12.rcl<-ecospat.rcls.grd(bio12,9)
B3B12.comb <- B12.rcl+B3.rcl*10
B3B12.prop_samples <- ecospat.recstrat_prop(B3B12.comb,100)
plot(B3B12.comb)
points(B3B12.prop_samples$x,B3B12.prop_samples$y,pch=16,cex=0.6,col=B3B12.prop_samples$class)
cleanEx()
nameEx("ecospat.recstrat_regl")
### * ecospat.recstrat_regl
flush(stderr()); flush(stdout())
### Name: ecospat.recstrat_regl
### Title: Random Ecologically Stratified Sampling of equal numbers
### Aliases: ecospat.recstrat_regl
### ** Examples
library(raster)
library(classInt)
bio3<- raster(system.file("external/bioclim/current/bio3.grd",package="biomod2"))
bio12<- raster(system.file("external/bioclim/current/bio12.grd",package="biomod2"))
B3.rcl<-ecospat.rcls.grd(bio3,9)
B12.rcl<-ecospat.rcls.grd(bio12,9)
B3B12.comb <- B12.rcl+B3.rcl*10
B3B12.regl_samples <- ecospat.recstrat_prop(B3B12.comb,100)
plot(B3B12.comb)
points(B3B12.regl_samples$x,B3B12.regl_samples$y,pch=16,cex=0.6,col=B3B12.regl_samples$class)
cleanEx()
nameEx("ecospat.sample.envar")
### * ecospat.sample.envar
flush(stderr()); flush(stdout())
### Name: ecospat.sample.envar
### Title: Sample Environmental Variables
### Aliases: ecospat.sample.envar
### ** Examples
cleanEx()
nameEx("ecospat.testData")
### * ecospat.testData
flush(stderr()); flush(stdout())
### Name: ecospat.testData
### Title: Test Data For The Ecospat package
### Aliases: ecospat.testData
### ** Examples
data(ecospat.testData)
str(ecospat.testData)
dim(ecospat.testData)
names(ecospat.testData)
cleanEx()
nameEx("ecospat.testEnvRaster")
### * ecospat.testEnvRaster
flush(stderr()); flush(stdout())
### Name: ecospat.testEnvRaster
### Title: Test Environmental Rasters for The Ecospat package
### Aliases: ecospat.testEnvRaster
### ** Examples
## Not run:
##D fpath <- system.file("extdata", "ecospat.testEnvRaster.RData", package="ecospat")
##D load(fpath)
##D plot(env)
## End(Not run)
cleanEx()
nameEx("ecospat.testMdr")
### * ecospat.testMdr
flush(stderr()); flush(stdout())
### Name: ecospat.testMdr
### Title: Test Data For The ecospat.mdr function
### Aliases: ecospat.testMdr
### ** Examples
data(ecospat.testMdr)
str(ecospat.testMdr)
dim(ecospat.testMdr)
cleanEx()
nameEx("ecospat.testNiche")
### * ecospat.testNiche
flush(stderr()); flush(stdout())
### Name: ecospat.testNiche
### Title: Test Data For The Niche Overlap Analysis
### Aliases: ecospat.testNiche
### ** Examples
data(ecospat.testNiche)
dim(ecospat.testNiche)
names(ecospat.testNiche)
cleanEx()
nameEx("ecospat.testNiche.inv")
### * ecospat.testNiche.inv
flush(stderr()); flush(stdout())
### Name: ecospat.testNiche.inv
### Title: Test Data For The Niche Dynamics Analysis In The Invaded Range
### Of A Hypothetical Species
### Aliases: ecospat.testNiche.inv
### ** Examples
data(ecospat.testNiche.inv)
str(ecospat.testNiche.inv)
dim(ecospat.testNiche.inv)
names(ecospat.testNiche.inv)
cleanEx()
nameEx("ecospat.testNiche.nat")
### * ecospat.testNiche.nat
flush(stderr()); flush(stdout())
### Name: ecospat.testNiche.nat
### Title: Test Data For The Niche Dynamics Analysis In The Native Range Of
### A Hypothetical Species
### Aliases: ecospat.testNiche.nat
### ** Examples
data(ecospat.testNiche.nat)
str(ecospat.testNiche.nat)
dim(ecospat.testNiche.nat)
names(ecospat.testNiche.nat)
cleanEx()
nameEx("ecospat.testTree")
### * ecospat.testTree
flush(stderr()); flush(stdout())
### Name: ecospat.testTree
### Title: Test Tree For The Ecospat package
### Aliases: ecospat.testTree
### ** Examples
fpath <- system.file("extdata", "ecospat.testTree.tre", package="ecospat")
tree <- read.tree(fpath)
plot(tree)
cleanEx()
nameEx("ecospat.varpart")
### * ecospat.varpart
flush(stderr()); flush(stdout())
### Name: ecospat.varpart
### Title: Variation Partitioning For GLM Or GAM
### Aliases: ecospat.varpart
### ** Examples
library(rms)
data('ecospat.testData')
# data for Soldanella alpina and Achillea millefolium
data.Solalp<- ecospat.testData[c("Soldanella_alpina","ddeg","mind","srad","slp","topo")]
# glm models for Soldanella alpina
glm.Solalp1 <- glm("Soldanella_alpina ~ pol(ddeg,2) + pol(mind,2) + pol(srad,2)",
data = data.Solalp, family = binomial)
glm.Solalp2 <- glm("Soldanella_alpina ~ pol(slp,2) + pol(topo,2)",
data = data.Solalp, family = binomial)
ecospat.varpart (model.1= glm.Solalp1, model.2= glm.Solalp2, model.12= glm.Solalp2)
### * <FOOTER>
###
cleanEx()
options(digits = 7L)
base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
grDevices::dev.off()
###
### Local variables: ***
### mode: outline-minor ***
### outline-regexp: "\\(> \\)?### [*]+" ***
### End: ***
quit('no')
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