predcor {factorstochvol} | R Documentation |
Predicts correlation matrix
Description
predcor
simulates from the posterior predictive distribution
of the model-implied correlation matrix.
Usage
predcor(x, ahead = 1, each = 1)
Arguments
x |
Object of class |
ahead |
Vector of timepoints, indicating how many steps to predict ahead. |
each |
Single integer (or coercible to such) indicating how often should be drawn from the posterior predictive distribution for each draw that has been stored during MCMC sampling. |
Value
4-dimensional array containing draws from the predictive correlation distribution.
Note
Currently crudely implemented as a triple loop in pure R, may be slow.
See Also
Other predictors:
predcond()
,
predcov()
,
predh()
,
predloglikWB()
,
predloglik()
,
predprecWB()
Examples
set.seed(1)
sim <- fsvsim(series = 3, factors = 1) # simulate
res <- fsvsample(sim$y, factors = 1) # estimate
# Predict 1, 10, and 100 days ahead:
predobj <- predcor(res, ahead = c(1, 10, 100))
# Trace plot of draws from posterior predictive distribution
# of the correlation of Sim1 and Sim2:
# (one, ten, and 100 days ahead):
plot.ts(predobj[1,2,,])
# Smoothed kernel density estimates of predicted covariance
# of Sim1 and Sim2:
plot(density(predobj[1,2,,"1"], adjust = 2))
lines(density(predobj[1,2,,"10"], adjust = 2), col = 2)
lines(density(predobj[1,2,,"100"], adjust = 2), col = 3)
[Package factorstochvol version 1.1.0 Index]