Common Extractors for 'svdraws' and 'svpredict' Objects
Some simple extractors returning the corresponding element of an
svdraws and svpredict object.
para(x, chain = "concatenated") latent0(x, chain = "concatenated") latent(x, chain = "concatenated") vola(x, chain = "concatenated") svbeta(x, chain = "concatenated") svtau(x, chain = "concatenated") priors(x) thinning(x) runtime(x) sampled_parameters(x) predy(y, chain = "concatenated") predlatent(y, chain = "concatenated") predvola(y, chain = "concatenated")
x |
|
chain |
optional either a positive integer or the string
|
y |
|
The return value depends on the actual funtion.
para(x, chain = "concatenated") |
extracts the parameter draws. |
latent(x, chain = "concatenated") |
extracts the latent contemporaneous log-volatility draws. |
latent0(x, chain = "concatenated") |
extracts the latent initial log-volatility draws. |
svbeta(x, chain = "concatenated") |
extracts the linear regression coefficient draws. |
svtau(x, chain = "concatenated") |
extracts the tau draws. |
vola(x, chain = "concatenated") |
extracts standard deviation draws. |
priors(x) |
extracts the prior
parameters used and returns them in a |
thinning(x) |
extracts the thinning parameters used and returns them in
a |
runtime(x) |
extracts the runtime and returns it as a
|
sampled_parameters(x) |
returns the names of time independent model
parameters that were actually sampled by |
predlatent(y, chain = "concatenated") |
extracts the predicted latent contemporaneous log-volatility draws. |
predvola(y, chain = "concatenated") |
extracts predicted standard deviation draws. |
predy(y, chain = "concatenated") |
extracts the predicted observation draws. |
Functions that have input parameter chain return
an mcmc.list object if chain=="all" and
return an mcmc object otherwise. If chain is
an integer, then the specified chain is selected from
all chains. If chain is "concatenated",
then all chains are merged into one mcmc object.
# Simulate data
sim <- svsim(150)
# Draw from vanilla SV
draws <- svsample(sim, draws = 2000)
## Summarize all parameter draws as a merged mcmc object
summary(para(draws))
## Extract the draws as an mcmc.list object
para(draws, chain = "all")
## Further short examples
summary(latent0(draws))
summary(latent(draws))
summary(vola(draws))
sampled_parameters(draws)
priors(draws)
# Draw 3 independent chains from heavy-tailed and asymmetric SV with AR(2) structure
draws <- svsample(sim, draws = 20000, burnin = 3000,
designmatrix = "ar2",
priornu = 0.1, priorrho = c(4, 4),
n_chains = 3)
## Extract beta draws from the second chain
svbeta(draws, chain = 2)
## ... tau draws from all chains merged/concatenated together
svtau(draws)
## Create a new svdraws object from the first and third chain
second_chain_excluded <- draws[c(1, 3)]
# Draw from the predictive distribution
pred <- predict(draws, steps = 2)
## Extract the predicted observations as an mcmc.list object
predicted_y <- predy(pred, chain = "all")
## ... the predicted standard deviations from the second chain
predicted_sd <- predvola(pred, chain = 2)
## Create a new svpredict object from the first and third chain
second_chain_excluded <- pred[c(1, 3)]Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.