Nothing
## ----, warning=FALSE, message=FALSE--------------------------------------
library(EcoSimR) # load EcoSimR library
set.seed(56) # for reproducible results
## ----, echo=FALSE, results='asis'----------------------------------------
knitr::kable(dataRodents, caption='Average body sizes of Sonoran desert rodents. Data from Brown (1975)')
## ----, echo=FALSE, fig.height=4,fig.width=4,fig.align='center'-----------
myModel <- cooc_null_model(dataWiFinches,suppressProg=TRUE)
plot(myModel,type="hist")
## ----, fig.height=8,fig.width=4,fig.align='center'-----------------------
myModel <- size_null_model(dataRodents,suppressProg=TRUE)
plot(myModel,type="size")
## ----, eval=FALSE--------------------------------------------------------
#
# speciesData # user must supply a data frame; speciesData=dataWiFinches for default run
# algo = "size_uniform" # randomize interior species with a uniform distribution
# metric = "var_ratio" # variance of size ratios of adjacent species
# nReps = 1000 # number of null assemblage created
# rowNames=TRUE # reads speciesData as a data frame wtih row labels in the first column
# saveSeed=FALSE # if TRUE, saves random number seed
# burn_in=500 # number of burn-in iterations for sim9
# algoOpts=list() # list of other specific options for the algorithm (used for size_source_pool)
# metricOpts=list() # list of other specific options for the metric
# suppressProg= FALSE # suppress printing of progress bar (for creating markdown files)
## ----, fig.height=4,fig.width=4,fig.align='center'-----------------------
# run default settings and show all output
myModel <- size_null_model(speciesData=dataRodents,suppressProg=TRUE)
summary(myModel)
plot(myModel,type = "hist")
## ----,fig.height=8,fig.width=4,fig.align='center'------------------------
plot(myModel,type="size") # throws error in vignette: figure margins too large
## ----, fig.height=4,fig.width=4,fig.align='center'-----------------------
# test for minimum size differences with a source pool model
# create a source pool of the rodent body sizes plus 20 other species
mySource <-c(dataRodents$Sonoran,as.double(sample(150,20)))
# create an arbitrary set of probabilty weights
myProbs <- runif(26)
# run the model
myModel <- size_null_model(speciesData=dataRodents,suppressProg=TRUE,
metric="min_diff",algo="size_source_pool",
algoOpts=list(sourcePool=mySource,speciesProbs=myProbs))
# show the results
summary(myModel)
plot(myModel,type="hist")
## ----, fig.height=8,fig.width=4,fig.align='center'-----------------------
plot(myModel,type="size")
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