Skip to contents

StCokriging: ordinary space-time cokriging of variable 0 under a separable intrinsic coregionalisation with exponential space and time correlations. DiffusionStCovariance: covariance of a Gaussian field propagated by the diffusion equation. Identical to the Python arm morie.fn.stcokrig.

Usage

StCokriging(
  coords,
  times,
  variable,
  values,
  targets,
  target_times,
  coreg,
  range_s,
  range_t,
  nugget = c(0, 0)
)

DiffusionStCovariance(h, u, sigma2 = 1, xi = 1, diffusivity = 1, dim = 2)

Arguments

coords

Observation coordinates (two-column).

times

Observation times.

variable

Variable index (0 or 1) of each observation.

values

Observed values.

targets

Prediction coordinates.

target_times

Prediction times.

coreg

2 by 2 coregionalisation matrix.

range_s, range_t

Exponential ranges.

nugget

Nuggets of the two variables.

h, u

Spatial and temporal lags.

sigma2, xi

Initial variance and correlation length.

diffusivity

Diffusion coefficient.

dim

Spatial dimension.

Value

A list, or the covariance values.

References

Kolovos, A., Christakos, G., Hristopulos, D. T. and Serre, M. L. (2004). Methods for generating non-separable spatiotemporal covariance models. Advances in Water Resources 27, 815-830.

Wackernagel, H. (2003). Multivariate Geostatistics, 3rd edn. Springer.

Examples

DiffusionStCovariance(1, 0.5, 2, 1, 0.5)
#> [1] 0.6065307