StModelVariogram: separable, product-sum, metric and sum-metric
variograms in the parametrisation of gstat::vgmST (marginals are
lists psill, model (Exp, Gau, Sph, Lin), range,
nugget). StCovarianceFamily: Gneiting (2002), Cressie-Huang (1999),
Iaco-Cesare (De Iaco, Myers and Posa 2002), periodic, separable
exponential and Porcu (Porcu, Gregori and Mateu 2006, quasi-arithmetic
mean: (0.5 (1 + (h/scale_s)^power_s)^sep + 0.5 (1 +
(|u|/scale_t)^power_t)^sep)^(-1/sep); at sep = 0 the continuous
limit, the separable geometric mean, or with method = "GeoModels"
the package's squared product) covariances. StLinearCombination: nonnegative
combinations. Identical to the Python arm morie.fn.stcovar.
Usage
StModelVariogram(
h,
u,
model,
space = NULL,
time = NULL,
joint = NULL,
sill = NULL,
k = NULL,
stani = NULL
)
StCovarianceFamily(h, u, family, ...)
StLinearCombination(h, u, components, weights)Arguments
- h
Spatial distances.
- u
Time lags.
- model
"separable","productSum","metric"or"sumMetric".- space, time, joint
Marginal structures.
- sill
Separable sill.
- k
Product-sum parameter.
- stani
Space-time anisotropy.
- family
Covariance family.
- ...
Family parameters.
- components
List of
list(family, params).- weights
Nonnegative weights.
References
Gneiting, T. (2002). Nonseparable, stationary covariance functions for space-time data. JASA 97, 590-600.
Cressie, N. and Huang, H.-C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. JASA 94, 1330-1340.
Graeler, B., Pebesma, E. and Heuvelink, G. (2016). Spatio-temporal interpolation using gstat. The R Journal 8, 204-218.
Porcu, E., Gregori, P. and Mateu, J. (2006). Nonseparable stationary anisotropic space-time covariance functions. SERRA 21, 113-122.
Examples
s <- list(psill = 2, model = "Exp", range = 100)
tm <- list(psill = 3, model = "Sph", range = 5)
StModelVariogram(c(0, 50, 120), c(1, 3, 10), "productSum", space = s, time = tm, k = 0.1)
#> [1] 1.065600 3.687244 4.997612
StCovarianceFamily(1, 2, "gneiting", a = 1, alpha = 0.5, beta = 1, gamma = 0.5, c = 1, tau = 1)
#> [1] 0.187128