paRaoP: Parallelized Parametric Rao's index of quadratic entropy (Q)

In rasterdiv: Diversity Indices for Numerical Matrices

Parallelized Parametric Rao's index of quadratic entropy (Q)

Description

This function computes the parametric Rao's index of quadratic entropy (Q), a measure of biodiversity that considers the evolutionary distances between species, utilizing parallel computing for enhanced performance. The computation is applied over a moving window across the input data.

Usage

paRaoP(
  x,
  alpha,
  window,
  dist_m,
  na.tolerance,
  diag,
  debugging,
  isfloat,
  mfactor,
  np,
  progBar
)

Arguments

x	Matrix or data frame; the input data over which the index calculation is performed.
alpha	Numeric; specifies the alpha value for the order of diversity in Hill's Index.
window	Numeric; half of the side length of the square moving window used in the calculation.
dist_m	Character; specifies the type of distance metric used in calculations.
na.tolerance	Numeric; the threshold proportion of NA values allowed in the moving window. If exceeded, the calculation for that window is skipped. Values range from 0.0 (no tolerance) to 1.0.
diag	Logical; indicates whether the diagonal of the distance matrix should be included in the computation. Typically set to FALSE.
debugging	Logical; set to FALSE by default. If TRUE, additional console messages will be displayed for debugging purposes.
isfloat	Logical; indicates whether the input data values are floating-point numbers.
mfactor	Integer; multiplication factor in case of input data as float numbers.
np	Number of processes for parallel computation.
progBar	logical. If TRUE a progress bar is shown.

Value

A list of matrices corresponding to the computed Rao's index values. Each matrix in the list represents the calculations performed over the moving window, with dimensions equal to dim(x).

Author(s)

Duccio Rocchini [e-mail], Matteo Marcantonio [e-mail]

See Also

paRao for the related non-parallelized function.

rasterdiv documentation built on April 4, 2025, 4:30 a.m.