griddedVgram | R Documentation |
Find (and plot) variograms for each field in a gridded verification set.
griddedVgram(object, zero.in = TRUE, zero.out = TRUE, time.point = 1,
obs = 1, model = 1, ...)
## S3 method for class 'griddedVgram'
plot(x, ... )
object |
list object of class “SpatialVx” containing information on the verification set. |
zero.in , zero.out |
logical, should the variogram be calculated over the entire field (zero.in), and/or over only the non-zero values (zero.out)? |
x |
list object as returned by |
time.point |
numeric or character indicating which time point from the “SpatialVx” verification set to select for analysis. |
obs , model |
numeric indicating which observation/forecast model to select for the analysis. |
... |
In the case of |
Here, the terms semi-variogram and variogram are used interchangeably.
This is a simple wrapper function to vgram.matrix
(entire field) from fields and/or variogram.matrix
(non-zero grid points only) for finding the variogram between two gridded fields. It calls this function for each of two fields in a verification set. This function allows one to do the diagnostic analysis proposed in Marzban and Sangathe (2009).
A list object containing the entire list passed in by the object argument, and components:
Vx.cgram.matrix , Fcst.vgram.matrix |
list objects as returned by vgram.matrix containing the variogram information for each field. |
No value is returned by plot.griddedVgram, plots are created showing the empirical variogram (circles), along with directional empirical variograms (dots), and the variogram by direction (image plot).
Eric Gilleland
Marzban, C. and Sandgathe, S. (2009) Verification with variograms. Wea. Forecasting, 24 (4), 1102–1120, doi:10.1175/2009WAF2222122.1.
vgram.matrix
, make.SpatialVx
data( "ExampleSpatialVxSet" )
x <- ExampleSpatialVxSet$vx
xhat <- ExampleSpatialVxSet$fcst
hold <- make.SpatialVx( x, xhat, field.type = "contrived",
units="none", data.name = "Example", obs.name = "x",
model.name = "xhat" )
res <- griddedVgram( hold, R = 8 )
plot( res )
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