Variogram extras

SampleVariogramNd: n-dimensional, optionally directional sample variogram (classical, madogram, rodogram or cross). AnisotropicLag: GSLIB 3-D geometric anisotropy. ZonalSemivariance: nested zonal anisotropy. VariogramEnvelope: permutation or bootstrap envelopes. VariogramJackknife: delete-one jackknife standard errors. VariogramCloudBox: variogram-cloud box statistics. VariogramFractal: Hurst exponent and fractal dimension. WindowedSemivariance: temporal semivariance in moving windows. Identical to the Python arm morie.fn.vgextra.

Usage

SampleVariogramNd(
  z,
  coords,
  boundaries,
  estimator = "classical",
  direction = NULL,
  tol = 22.5,
  z2 = NULL
)

AnisotropicLag(h, azimuth = 0, dip = 0, rake = 0, ratio1 = 1, ratio2 = 1)

ZonalSemivariance(h, model, zonal_model, axis = 3)

VariogramEnvelope(
  z,
  coords,
  boundaries,
  nsim = 99,
  level = 0.95,
  method = "permutation",
  seed = 1
)

VariogramJackknife(z, coords, boundaries)

VariogramCloudBox(z, coords, boundaries)

VariogramFractal(dist, gamma, dim = 1, max_lag = NULL)

WindowedSemivariance(series, lags, window, step = 1)

Arguments

z, z2

Data values.

coords

Coordinate matrix (any dimension).

boundaries

Lag-bin boundaries.

estimator

Estimator.

direction

Direction vector.

tol

Angular tolerance (degrees).

h

Separation vector.

azimuth, dip, rake

Rotation angles (degrees).

ratio1, ratio2

Anisotropy ratios.

model, zonal_model

Variogram models (see VgmSemivariance).

axis

Zonal axis (1-based).

nsim

Number of simulations.

level

Envelope level.

method

"permutation" or "bootstrap".

seed

Philox seed.

dist, gamma

Lags and semivariances.

dim

Embedding dimension.

max_lag

Largest lag in the fit.

series

Time series.

lags

Integer lags.

window, step

Window length and step.

Value

List or numeric.

References

Deutsch, C. V. and Journel, A. G. (1998). GSLIB, 2nd ed. Oxford University Press.

Diggle, P. J. and Ribeiro, P. J. (2007). Model-based Geostatistics. Springer.

Shafer, J. M. and Varljen, M. D. (1990). Approximation of confidence limits on sample semivariograms from single realizations of spatially correlated random fields. Water Resources Research 26, 1787-1802.

Examples

SampleVariogramNd(c(1, 2, 4), rbind(c(0, 0, 0), c(1, 0, 0), c(2, 0, 0)), c(0, 1.5, 2.5))$gamma
#> [1] 1.25 4.50
AnisotropicLag(c(1, 0, 0), ratio1 = 0.5)
#> [1] 2