causal_filter: Causal Filtering

In langendorfr/DMMS: Tracking and Forecasting Interactions in Real Time

Description

Filters data with supplied probabilities of causality. This can serve a priori in place of post-hoc model selection.

Usage

causal_filter(data, causal_probs, iterations)

Arguments

data	Data.
causal_probs	Causal probabilities, or 1 - p-values from a test for causality, for each interactor (column in the data).
iteractions	Number of times to apply the causal filter.

Value

Values in the Jacobian.

langendorfr/DMMS documentation built on May 14, 2019, 2:55 p.m.