cov_estim_precond_sf: Covariance Estimation after Preconditioning with a Single...

In antshi/CovEstim: (High-dimensional) Covariance Estimation

Covariance Estimation after Preconditioning with a Single Factor Model

Description

Computes a specific estimator of the covariance matrix after preconditioning the data with a Single Factor (SF) model - the implicit market portfolio.

Usage

cov_estim_precond_sf(data, zeromean_log = FALSE, precond_est_func = NULL, ...)

Arguments

data	an nxp data matrix.
zeromean_log	a logical, indicating whether the data matrix has zero means (TRUE) or not (FALSE). Default value is FALSE.
precond_est_func	a function for estimating the precondtioned covariance matrix.
...	further arguments to be parsed to precond_est_func

Value

a list with the following entries

• a pxp estimated covariance matrix.

• an estimation specific tuning parameter, here the bandwidth speed.

References

\insertAllCited

Examples

data(rets_m)
sigma_lwnl_sf <- cov_estim_precond_sf(rets_m,
  precond_est_func = cov_estim_lwnl, bandwidth_speed = NULL
)[[1]]
sigma_glasso_sf <- cov_estim_precond_sf(rets_m,
  precond_est_func = cov_estim_glasso, rho = 0.01
)[[1]]

antshi/CovEstim documentation built on June 10, 2025, 3:11 a.m.