bwCov: Covariance Bandwidth Calculation by Cross-Validation
bwCov calculates a single bandwidth to estimate the time-varying variance-
covariance matrix.
Description
Covariance Bandwidth Calculation by Cross-Validation
bwCov calculates a single bandwidth to estimate the time-varying variance-
covariance matrix.
Usage
bwCov(
x,
z = NULL,
cv.block = 0,
est = c("lc", "ll"),
tkernel = c("Triweight", "Epa", "Gaussian")
)
Value
A scalar.
Arguments
x
A matrix or a data frame.
z
A vector with the variable over which coefficients are smooth over.
cv.block
A positive scalar with the size of the block in leave-one block-out cross-validation.
By default 'cv.block=0' meaning leave-one-out cross-validation.
est
The nonparametric estimation method, one of "lc" (default) for linear constant
or "ll" for local linear.
tkernel
A character, either "Triweight" (default), "Epa" or "Gaussian" kernel function.
data(CEES)
## Using a shorter set for a quick example. Variable "Date" is removed.mydata <- tail (CEES[, -1], 50)
bw.cov <- bwCov(mydata)
Sigma.hat <- tvCov(mydata, bw = bw.cov)