SpatialVx

Spatial Forecast Verification

Spatial forecast verification arose from verifying high-resolution forecasts, where coarser-resolution models generally are favored even when a human forecaster finds the higher-resolution model to be considerably better. Most newly proposed methods, which largely come from image analysis, computer vision, and similar, are available, with more on the way.

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Description file content

Package
SpatialVx
Version
0.6-5
Date
2019-06-10
Title
Spatial Forecast Verification
Author
Eric Gilleland
Maintainer
Eric Gilleland
Depends
R (>= 2.10.0), spatstat (>= 1.37-0), fields (>= 6.8), smoothie, smatr, turboEM
Imports
distillery, maps, boot, CircStats, fastcluster, waveslim
Description
Spatial forecast verification arose from verifying high-resolution forecasts, where coarser-resolution models generally are favored even when a human forecaster finds the higher-resolution model to be considerably better. Most newly proposed methods, which largely come from image analysis, computer vision, and similar, are available, with more on the way.
License
GPL (>= 2)
URL
BugReports
http://www.ral.ucar.edu/staff/ericg
NeedsCompilation
no
Packaged
2019-06-10 15:46:47 UTC; eric
Repository
CRAN
Date/Publication
2019-06-11 17:10:02 UTC

install.packages('SpatialVx')

0.6-5

4 days ago

http://www.ral.ucar.edu/projects/icp/SpatialVx

Eric Gilleland

GPL (>= 2)

Depends on

R (>= 2.10.0), spatstat (>= 1.37-0), fields (>= 6.8), smoothie, smatr, turboEM

Imports

distillery, maps, boot, CircStats, fastcluster, waveslim

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