![]() "smooth" returns the kernel smoothed variogram. A case of particular interest is lambda = 0ĭefines the output type: the options "bin" returns values ofīinned variogram, "cloud" returns the variogram cloud and ![]() If another value is provided the variogram isĭata. Values of the Box-Cox transformation parameter. See documentation of trend.spatial for further details. See DETAILS below for more details on how to specify the bins.Ī vector with values to define the variogram binning. If a matrix is provided, each column is regarded as one variable or realization.Ī vector with values used to define the variogram binning. Typically an object of the classĬoordinates of the n data locations in each row. Variog.dist ( geodata, coords = geodata $ coords, data = geodata $ data, uvec = "default", breaks = "default", trend = "cte", lambda = 1, option = c ( "bin", "cloud", "smooth" ), estimator.type = c ( "classical", "modulus" ), nugget.tolerance, max.dist, dist.mat, pairs.min = 2, bin.cloud = FALSE, direction = "omnidirectional", tolerance = pi / 8, unit.angle = c ( "radians", "degrees" ), angles = FALSE, messages. sph2car: Computes cartesian coordinates from long,lat geographical.Pt2Pts.wo.obstacle: Calculate distance from one point to a set of points using.Prep_loc_dist: Prepare loc.dist for idw special case.Modified from function nv in geoR library. : Special case idw for reduced time calculation.idw.dist: Inverse distance calculation using custom distances..obstacle: Find neighbours without obstacles in different directions.eyefit.large: Eyefit function of geoR with higher range for phi and sigma.distref.raster-class: Class for distref.raster.distref.raster: Transfrom reference raster as a network of paths for distance.distref.data-class: Class for distref.data. ![]() distref.data: Get characteristics of data regarding the reference raster.dist.obstacle: Calculate 2D distances from points to points avoiding.autofitVariogram.dist: Automatically fitting a variogram.
0 Comments
Leave a Reply. |