sgsR (version 1.5.0)

calculate_pop: Population descriptors

Description

Population matrices and descriptions of metric raster data

Calculates population level statistics including principal components, quantile matrix, and covariance matrix needed necessary for calculate_lhsOpt. Outputs can also be used as an input for sample_ahels.

Usage

calculate_pop(mraster, PCA = FALSE, matQ = TRUE, nQuant = 10, matCov = TRUE)

Value

List of matrices to be used as input for calculate_lhsOpt.

Arguments

mraster

spatRaster. ALS metrics raster.

PCA

Logical. Calculates principal component loadings of the population for PCA similarity factor testing. default = FALSE.

matQ

Logical. Calculates quantile matrix of the population for quantile comparison testing. default = TRUE.

nQuant

Numeric. Number of quantiles to divide the population into for matQ. default = 10.

matCov

Logical. Calculates covariate matrix of the population. Needed for Kullback–Leibler divergence testing. default = TRUE. Requires matQ = TRUE.

Author

Tristan R.H. Goodbody

References

Malone BP, Minasny B, Brungard C. 2019. Some methods to improve the utility of conditioned Latin hypercube sampling. PeerJ 7:e6451 DOI 10.7717/peerj.6451

See Also

Other calculate functions: calculate_allocation(), calculate_allocation_existing(), calculate_coobs(), calculate_distance(), calculate_pcomp(), calculate_representation(), calculate_sampsize()

Examples

#--- Load raster and access files ---#
r <- system.file("extdata", "mraster.tif", package = "sgsR")
mr <- terra::rast(r)

calculate_pop(mraster = mr)