predloglik {factorstochvol} | R Documentation |
Evaluates the predictive log likelihood using the predicted covariance matrix
Description
predloglik
approximates the predictive log likelihood by
simulating from the predictive distribution of the covariance
matrix and evaluating the corresponding multivariate normal
distribution.
Usage
predloglik(
x,
y,
ahead = 1,
each = 1,
alldraws = FALSE,
indicator = rep(TRUE, ncol(y))
)
Arguments
x |
Object of class |
y |
Matrix of dimension |
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. |
alldraws |
Should all the draws be returned or just the final results? (Can be useful to assess convergence.) |
indicator |
Logical vector of length |
Value
Vector of length length(ahead)
with log predictive
likelihoods.
See Also
Uses predcov
. If m
is large
but only few factors are used, consider also using
predloglikWB
.
Other predictors:
predcond()
,
predcor()
,
predcov()
,
predh()
,
predloglikWB()
,
predprecWB()
Examples
set.seed(1)
# Simulate a time series of length 1100:
sim <- fsvsim(n = 1100, series = 3, factors = 1)
y <- sim$y
# Estimate using only 1000 days:
res <- fsvsample(y[seq_len(1000),], factors = 1)
# Evaluate the 1, 10, and 100 days ahead predictive log
# likelihood:
ahead <- c(1, 10, 100)
scores <- predloglik(res, y[1000+ahead,], ahead = ahead, each = 10)
print(scores)