You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
As it is recommended to drop the initial samples in produced by a (CO)VLMC when used for bootstrap estimation, it would be convenient to have this feature implemented directly by simulate.vlmc(). For simulate.covlmc() the situation is much more complex as covariates are needed.
The text was updated successfully, but these errors were encountered:
The case of covlmc is too complex to be handled automatically. For a programming point of view, this only marginally more complex than for VLMC, but on a mathematical point of view, this is far from obvious. Indeed COVLMC are not stationary as they are driven by the external covariates. This aiming to the stationary distribution is at best misguided.
As it is recommended to drop the initial samples in produced by a (CO)VLMC when used for bootstrap estimation, it would be convenient to have this feature implemented directly by
simulate.vlmc()
. Forsimulate.covlmc()
the situation is much more complex as covariates are needed.The text was updated successfully, but these errors were encountered: