Prepare knot locations for Hmsc GPP models — prepare

Prepare the locations of knots for use in Gaussian Predictive Process (GPP) models within the HMSC framework. It ensures that knots are spaced at a minimum specified distance and applies jitter to any identical coordinates to avoid overlap.

Usage

prepare_knots(
  coordinates = NULL,
  min_distance = NULL,
  jitter_distance = 100,
  min_lf = NULL,
  max_lf = NULL,
  alphapw = list(Prior = NULL, Min = 10, Max = 1500, Samples = 101)
)

Arguments

coordinates: Numeric matrix or data frame containing the (x, y) coordinates of sampling units.
min_distance: Numeric. Minimum distance between knots in meters. This distance is used for both knotDist and minKnotDist parameters of the Hmsc::constructKnots function.
jitter_distance: Numeric. The jitter distance applied to overlapping coordinates to avoid exact duplicates. Defaults to 100 meters.
min_lf, max_lf: Integer. Minimum and maximum number of latent factors to be used. Both default to NULL which means that the number of latent factors will be estimated from the data. If either is provided, the respective values will be used as arguments to Hmsc::setPriors.
alphapw: Prior for the alpha parameter. Defaults to a list with Prior = NULL, Min = 10, Max = 1500, and Samples = 101. If alphapw is NULL or a list with all NULL list items, the default prior will be used. If Prior is a matrix, it will be used as the prior. If Prior = NULL, the prior will be generated using the minimum and maximum values of the alpha parameter (min and max, respectively; in kilometre) and the number of samples (Samples). Defaults to a prior with 101 samples ranging from 10 to 1500 km, with the first value in the second column set to 0.5.

Value

An object of class HmscRandomLevel, suitable for specifying the random level in HMSC GPP models. This object contains the prepared knot locations as a data frame with columns var_1 and var_2 (numeric coordinates), after possible jittering and conversion to avoid overlap.

Author

Ahmed El-Gabbas