fit_pdfsp: Fit the species 'pdfs'.

In mchevalier2/crestr: A Probabilistic Approach to Reconstruct Past Climates Using Palaeoecological Datasets

Fit the species pdfs.

Description

Fit the species pdfs.

Usage

fit_pdfsp(
  climate,
  ccs,
  bin_width,
  shape,
  xrange,
  use_ccs = TRUE,
  climateSpaceWeighting.type = "linear"
)

Arguments

climate	A vector of climatic values where the species is present.
ccs	A ccs object returned by calib_clim_space.
bin_width	The width of the bins used to correct for unbalanced climate state. Use values that split the studied climate gradient in 15-25 classes (e.g. 2°C for temperature variables). Default is 1.
shape	The imposed shape of the species pdfs. We recommend using 'normal' for temperature variables and 'lognormal' for the variables that can only take positive values, such as precipitation or aridity. Default is 'normal' for all.
xrange	The climate gradient upon which the pdf with be defined.
use_ccs	Boolean to indicate if the pdfsp should be corrected by the distribution of the modern climate space
climateSpaceWeighting.type	A correction factor for the clame space weighting correction to limit the edge effects. Either 'linear' (default), 'sqrt' or 'log'.

Value

The pdf of the species.

Examples

# Creating one randomised species
climate_species <- round(stats::rnorm(50, 15, 2), 1)

# Creating one randomised climate space
climate_space <- base::sample(0:300 / 10, 4000, replace = TRUE)

ccs <- calib_clim_space(climate_space, 2)
xrange <- fit_xrange(ccs, "normal", 2)
pdfsp <- fit_pdfsp(climate_species, ccs, 2, "normal", xrange)
plot(xrange, pdfsp, type = "l")

# Testing that the area under the curve is equal to 1.
all.equal(sum(pdfsp * (xrange[2] - xrange[1])), 1)

mchevalier2/crestr documentation built on Feb. 14, 2025, 6:31 p.m.