sigma_estim_precond: Covariance Estimation - Preconditioned

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

Description

Computes a specific estimator of the covariance matrix after preconditioning the data with a single factor model - the implicit market portfolio.

Usage

sigma_estim_precond(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

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Examples

data(sp200)
sp_rets <- sp200[,-1]
sigma_lwnl_sf <- sigma_estim_precond(sp_rets,
precond_est_func=sigma_estim_lwnl, bandwidth_speed=NULL)[[1]]
sigma_glasso_sf <- sigma_estim_precond(sp_rets,
precond_est_func=sigma_estim_glasso, rho=0.01)[[1]]

antshi/CovEstim documentation built on Nov. 13, 2020, 2:25 p.m.