makeQuantileSimulationSurface {isocat} | R Documentation |
Create quantile-simulation surfaces
Description
Converts normalized probability surfaces (e.g. one layer output of isotopeAssignmentModel function) to quantile surfaces.
Usage
makeQuantileSimulationSurface(
probabilitySurface,
ValidationQuantiles,
rename = FALSE,
rescale = TRUE
)
Arguments
probabilitySurface |
Normalized probability surface RasterLayer. |
ValidationQuantiles |
Vector of quantile values from known-origin individuals, against which to compare each value within the probability surface. Each value must be between 0 and 1. |
rename |
Character value to append to raster name (e.g. "_quantileSimulation"). Defaults to FALSE. |
rescale |
If rescale = TRUE, returns surface showing proportion of times each surface cell value fell within the validation quantiles distribution. If rescale = FALSE, returns discrete number of times the cell fell within the distribution. |
Value
Returns RasterLayer rescaled to quantile values.
Examples
# Generate example probability surfaces.
library(isocat)
myiso <- raster::rasterFromXYZ(isoscape)
myiso_sd <- raster::rasterFromXYZ(isoscape_sd)
df <- data.frame(
ID = c(-100, -80, -50),
isotopeValue = c(-100, -80, -50),
SD_indv = rep(5, 3)
)
assignmentModels <- isotopeAssignmentModel(
ID = df$ID,
isotopeValue = df$isotopeValue,
SD_indv = df$SD_indv,
precip_raster = myiso,
precip_SD_raster = myiso_sd
)
# Example known-origin quantile data.
q <- rweibull(20000, 6, .98)
q <- sample( q[ q >=0 & q <= 1 ], 10000, replace = TRUE)
hist(q)
# Convert to quantile surfaces.
quantileSimulation_surface <- raster::stack(
lapply(
unstack(assignmentModels),
makeQuantileSimulationSurface,
ValidationQuantiles = q)
)
plot(quantileSimulation_surface)
[Package isocat version 0.3.0 Index]