stepwise.forward: Stepise forward non-exhaustive greedy search, calculates the...

In multdyn: Multiregression Dynamic Models

Description

Stepise forward non-exhaustive greedy search, calculates the optimum value of the discount factor.

Usage

stepwise.forward(Data, node, nbf = 15, delta = seq(0.5, 1, 0.01),
  max.break = TRUE, priors = priors.spec())

Arguments

Data	Dataset with dimension number of time points T x number of nodes Nn.
node	The node to find parents for.
nbf	The Log Predictive Likelihood will sum from (and including) this time point.
delta	A vector of values for the discount factor.
max.break	If TRUE, the code will break if adding / removing parents does not improve the LPL. If FALSE, the code will continue to the zero parent / all parent model. Default is TRUE.
priors	List with prior hyperparameters.

Value

model.store The parents, LPL and chosen discount factor for the subset of models scored using this method.

multdyn documentation built on May 2, 2019, 3:43 p.m.