tscoskew.gogarch.estimate {tsmarch} | R Documentation |
Coskewness Extractor
Description
Extracts the conditional coskewness matrices.
Usage
## S3 method for class 'gogarch.estimate'
tscoskew(
object,
index = NULL,
distribution = FALSE,
standardize = TRUE,
folded = TRUE,
...
)
## S3 method for class 'gogarch.predict'
tscoskew(
object,
index = NULL,
distribution = FALSE,
standardize = TRUE,
folded = TRUE,
...
)
## S3 method for class 'gogarch.simulate'
tscoskew(
object,
index = NULL,
distribution = FALSE,
standardize = TRUE,
folded = TRUE,
...
)
Arguments
object |
an object class from one of the models in the package. |
index |
the time index (integer) from which to extract a subset of the coskewness array rather than the whole time series. |
distribution |
whether to return the full simulated coskewness distribution for the predicted and simulated objects. |
standardize |
whether to standardize the 3th co-moment so that it represents the coskewness. |
folded |
whether to return the result as a folded or unfolded array. The folded array is n_series x n_series x n_series x horizon (x simulation if predicted or simulated object). The unfolded array is a n_series x (n_series^2) x horizon array. Calculations such as weighted co-moments are based on the unfolded array using the Kronecker operator. |
... |
none |
Details
The calculation of the coskewness array from the independent factors is very
expensive in terms of memory footprint as well as computation time.
While it does take advantage of multiple threads if required (see
setThreadOptions
), in the case of many series this
will quickly become difficult for systems low RAM. Because of this, there is
the option to extract a specific point in time output using the index
argument.
Value
the coskewness (see details).
Author(s)
Alexios Galanos