plotProbcast | R Documentation |
Produces contour, image, or perspective plot of a forecast using loess prediction on a grid.
plotProbcast( forecast, longitude, latitude, nGrid = 65, type = c("image", "contour", "persp"), ..., interpolate = FALSE, span = 0.75, maps = NULL)
forecast |
Numeric vector of forecasts. |
longitude |
Numeric vector giving the longitude of each forecast location. |
latitude |
Numeric vector giving the latitude of each forecast location. |
nGrid |
Number of grid points for |
type |
A character string indicating the desired plot type.
Should be one of either |
... |
Additional arguments to be passed to the plotting method. |
interpolate |
A logical variable indicating whether or not a |
span |
Smoothing parameter for |
maps |
A logical value indicating whether or not to include
a map outline. The default is to include an outline
if |
If the fields
library is loaded, a legend (and optionally
a map outline) will be included in image plots.
An image, contour, or perspective plot of the forecast.
C. Fraley, A. E. Raftery, T. Gneiting and J. M. Sloughter,
ensembleBMA
: An R
Package for Probabilistic Forecasting
using Ensembles and Bayesian Model Averaging,
Technical Report No. 516R, Department of Statistics, University of
Washington, 2007 (revised 2010).
quantileForecast
data(srft) labels <- c("CMCG","ETA","GASP","GFS","JMA","NGPS","TCWB","UKMO") srftData <- ensembleData( forecasts = srft[,labels], dates = srft$date, observations = srft$obs, latitude = srft$lat, longitude = srft$lon, forecastHour = 48, initializationTime = "00") ## Not run: # R check bmaFit <- ensembleBMA( srftData, date = "2004012900", trainingDays = 25, model = "normal") bmaForc <- quantileForecast( bmaFit, srftData, date = "2004012900", quantiles = c(.1, .5, .9)) obs <- srftData$date == "2004012900" lat <- srftData$latitude[obs] lon <- srftData$longitude[obs] plotProbcast( bmaForc[,"0.5"], lat, lon, type = "contour", interpolate = TRUE) title("Median Forecast") plotProbcast( srftData$obs[obs], lat, lon, type = "contour", interpolate = TRUE) title("Observed Surface Temperature") data(srftGrid) memberLabels <- c("CMCG","ETA","GASP","GFS","JMA","NGPS","TCWB","UKMO") srftGridData <- ensembleData(forecasts = srftGrid[,memberLabels], latitude = srftGrid[,"latitude"], longitude = srftGrid[,"longitude"], forecastHour = 48, initializationTime = "00") gridForc <- quantileForecast( bmaFit, srftGridData, date = "2004021400", quantiles = c( .1, .5, .9)) library(fields) plotProbcast(gridForc[,"0.5"],lon=srftGridData$lon, lat=srftGridData$lat,type="image",col=rev(rainbow(100,start=0,end=0.85))) title("Median Grid Forecast for Surface Temperature", cex = 0.5) probFreeze <- cdf( bmaFit, srftGridData, date = "2004021400", value = 273.15) plotProbcast(probFreeze, lon=srftGridData$lon, lat=srftGridData$lat, type="image",col=gray((32:0)/32)) title("Probability of Freezing", cex = 0.5) ## End(Not run)
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