## The pseudo-data within `crestr`
library(crestr)
data(crest_ex)
data(crest_ex_pse)
data(crest_ex_selection)
## the first 6 samples
head(crest_ex)
## the structure of the data frame
str(crest_ex)
crest_ex_pse
crest_ex_selection
## Application: Reconstructions using pseudo-data
### Data extraction and calibration
reconstr <- crest.get_modern_data( df = crest_ex, # The fossil data
pse = crest_ex_pse, # The proxy-species equivalency table
taxaType = 0, # The type of taxa is 0 for the example
climate = c("bio1", "bio12"), # The climate variables to reconstruct
selectedTaxa = crest_ex_selection, # The taxa to use for each variable
dbname = "crest_example", # The database to extract the data
verbose = FALSE # Print status messages
)
reconstr$inputs$selectedTaxa
reconstr
reconstr <- crest.calibrate( reconstr, # A crestObj produced at the previous stage
climateSpaceWeighting = TRUE, # Correct the PDFs for the heteregenous
# distribution of the modern climate space
bin_width = c(2, 50), # The size of bins used for the correction
shape = c("normal", "lognormal"), # The shape of the species PDFs
verbose = FALSE # Print status messages
)
plot_climateSpace(reconstr)
plot_taxaCharacteristics(reconstr, taxanames='Taxon2', climate='bio1', h0=0.2)
plot_taxaCharacteristics(reconstr, taxanames='Taxon6', climate='bio1', h0=0.2)
### Reconstruction and interpretation
reconstr <- crest.reconstruct( reconstr, # A crestObj produced at the previous stage
verbose = FALSE # Print status messages
)
names(reconstr)
lapply(reconstr$reconstructions, names)
head(reconstr$reconstructions$bio1$optima)
str(reconstr$reconstructions$bio1$optima)
signif(reconstr$reconstructions$bio1$likelihood[1:6, 1:6], 3)
str(reconstr$reconstructions$bio1$likelihood)
plot(reconstr, climate = 'bio1')
plot(reconstr, climate = 'bio12', simplify=TRUE, uncertainties=c(0.4, 0.6, 0.8))
export(reconstr, loc=tempdir(), dataname='crest-test')
list.files(file.path(tempdir(), 'crest-test'))
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