| plot.pred.density {BMS} | R Documentation |
Plots predictive densities for conditional forecasts of class 'pred.density'
## S3 method for class 'pred.density':
## S3 method for class 'pred.density'
plot(x, predict_index = NULL, addons = "eslz", realized.y = NULL,
addons.lwd = 1.5, ...)
x |
an object of class |
predict_index |
An integer vector detailing which forecasted observations (corresponding to the argument |
addons |
character, defaulting to |
realized.y |
A vector with realized values of the dependent variables to be plotted in addition to the predictive density, must have its length conforming to |
addons.lwd |
Line width to be used for the low-level plotting commands specified by |
... |
arguments to be passed on to |
The argument addons specifies what additional information should be added to the plot(s) via the low-level commands lines and legend:
"e" for the posterior expected value (EV) of the prediction,
"s" for 2 times its posterior standard deviation ('standard errors'),
"z" for a zero line,
"l" for including a legend
Any combination of these letters will give the desired result. Use addons="" for not using any of these.
Martin Feldkircher and Stefan Zeugner
pred.density for constructing predictive densities, bms for creating bma objects, density.bma for plotting coefficient densities
Check http://bms.zeugner.eu for additional help.
data(datafls) mm=bms(datafls,user.int=FALSE) #predictive density for two 'new' data points pd=pred.density(mm,newdata=datafls[1:2,]) #plot the density for the second forecast observation plot(pd,2) #plot the density with realized dep. variable, and no standard errors plot(pd, 1, realized.y=0,addons="lzeg")