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

Description Usage Arguments Value

View source: R/dgm.R

Description

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

Usage

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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.


schw4b/DGM documentation built on May 7, 2019, 3:16 p.m.