Reference
VAR
Vector autoregressive model
| VarOls | OLS for Vector autoregressive model |
| VarBayes | Bayesian Vector Autoregressive Model |
VHAR
Vector heterogeneous autoregressive model
| VharOls | OLS for Vector heterogeneous autoregressive model |
| VharBayes | Bayesian Vector Autoregressive Model |
Priors
Prior configuration
| SsvsConfig | SSVS prior configuration |
| HorseshoeConfig | Horseshoe prior configuration |
| MinnesotaConfig | Minnesota prior configuration |
| LambdaConfig | Hierarchical structure of Minnesota prior |
| NgConfig | Normal-Gamma prior configuration |
| DlConfig | Dirichlet-Laplace prior configuration |
| LdltConfig | Prior for Covariance Matrix |
| SvConfig | |
| InterceptConfig | Prior for Constant term |
Random
Random generation functions
| normal.generate_mnormal | generate_mnormal(arg0: typing.SupportsInt, arg1: typing.Annotated[numpy.typing.ArrayLike, numpy.float64, “[m, 1]”], arg2: typing.Annotated[numpy.typing.ArrayLike, numpy.float64, “[m, n]”], arg3: typing.SupportsInt, arg4: typing.SupportsInt) -> typing.Annotated[numpy.typing.NDArray[numpy.float64], “[m, n]”] |
Datasets
Datasets
| load_vix | Load and return the CBOE VIX of several ETF datasets |
Utility functions
Related to configuration
| checkomp.is_omp | is_omp() -> bool |
| checkomp.check_omp | check_omp() -> None |