inEllipsoid | R Documentation |
Determine if a point is inside or outside an ellipsoid.
inEllipsoid(centroid, eShape, env_data, level)
centroid |
A numeric vector of centroids for each environmental variable |
eShape |
Shape matrix of the ellipsoid (can be a covariance matrix or a minimum volume ellipsoid). |
env_data |
A data frame with the environmental training data. |
level |
Proportion of points to be included in the ellipsoids. This parameter is equivalent to the error (E) proposed by Peterson et al. (2008). |
A data.frame with 2 columns. The first "in_Ellipsoid" binary response with values 1 (inside the ellipsoid) and zeros (outside the ellipsoid); the second "mh_dist" Mahalanobis distance to centroid.
## Not run:
# Bioclimatic layers path
wcpath <- list.files(system.file("extdata/bios",
package = "ntbox"),
pattern = ".tif$",full.names = TRUE)
# Bioclimatic layers
wc <- raster::stack(wcpath)
# Occurrence data for the giant hummingbird (Patagona gigas)
pg <- utils::read.csv(system.file("extdata/p_gigas.csv",
package = "ntbox"))
# Environmental data
pg_env <- raster::extract(wc,pg[,c("longitude",
"latitude")],
df=TRUE)
pg_env <- pg_env[,-1]
pg_ellip <- cov_center(pg_env,mve=TRUE,
level=0.95,
vars = c("bio05",
"bio06",
"bio12"))
# Environmental random data
env_rdata <- raster::sampleRandom(wc,1000)
inErdata <- inEllipsoid(env_data = env_rdata[,c("bio05",
"bio06",
"bio12")],
centroid = pg_ellip$centroid,
eShape=pg_ellip$covariance,
level = 0.99)
## End(Not run)
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