gsi.EVario3D {gmGeostats} | R Documentation |
Empirical variogram or covariance function in 3D
Description
compute the empirical variogram or covariance function in a 3D case study
Usage
gsi.EVario3D(
X,
Z,
Ff = rep(1, nrow(X)),
maxdist = max(dist(X[sample(nrow(X), min(nrow(X), 1000)), ]))/2,
lagNr = 15,
lags = seq(from = 0, to = maxdist, length.out = lagNr + 1),
dirvecs = t(c(1, 0, 0)),
angtol = 90,
maxbreadth = Inf,
minpairs = 10,
cov = FALSE
)
Arguments
X |
matrix of Nx3 columns with the geographic coordinates |
Z |
matrix or data.frame of data with dimension (N,Dv) |
Ff |
for variogram, matrix of basis functions with nrow(Ff)=N (can be a N-vector of 1s; should include the vector of 1s!!); for covariance function, a (N,Dv)-matrix or a Dv-vector giving the mean values |
maxdist |
maximum lag distance to consider |
lagNr |
number of lags to consider |
lags |
if maxdist and lagNr are not specified, either: (a) a matrix of 2 columns giving minimal and maximal lag distance defining the lag classes to consider, or (b) a vector of lag breaks |
dirvecs |
matrix which rows are the director vectors along which variograms will be computed (these will be normalized!) |
angtol |
scalar, angular tolerance applied (in degrees; defaults to 90??, ie. isotropic) |
maxbreadth |
maximal breadth (in lag units) orthogonal to the lag direction (defaults to |
minpairs |
minimal number of pairs falling in each class to consider the calculation sufficient; defaults to 10 |
cov |
boolean, is covariance (TRUE) or variogram (FALSE) desired? defaults to variogram |
Value
An empirical variogram for the provided data. NOTE: avoid using directly gsi.* functions! They
represent either internal functions, or preliminary, not fully-tested functions. Use variogram
instead.
See Also
Other gmEVario functions:
as.gmEVario.gstatVariogram()
,
gsi.EVario2D()
,
ndirections()
,
plot.gmEVario()
,
variogramModelPlot()