beta.special.pcObj

x.pos

y.pos

pcObj

Covariance that was used in the pc-object fit

mcov

Matrices that can be precomputed,  if
  needed (see code for details on how to precompute)

amat,  amatSkel,  t.amat

This function is DEPRECATED! Use <code><a href="/link/ida?package=pcalg&version=2.0-3" rd-options="" data-mini-rdoc="pcalg::ida">ida</a></code> or
  <code><a href="/link/idaFast?package=pcalg&version=2.0-3" rd-options="" data-mini-rdoc="pcalg::idaFast">idaFast</a></code> instead.

multivariate

models

graphs

This package contains several functions for causal structure
  learning and causal inference using graphical models. The main algorithms
  for causal structure learning are PC (for observational data without hidden
  variables), FCI and RFCI (for observational data with hidden variables),
  and GIES (for a mix of observational and interventional data without hidden
  variables). For causal inference the IDA algorithm and the generalized
  backdoor criterion is implemented.

beta.special.pcObj: Compute set of intervention effects in a fast way

Description

Usage

Arguments

Value

See Also