Package edu.cmu.tetrad.algcomparison.simulation
package edu.cmu.tetrad.algcomparison.simulation
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ClassDescriptionThis class represents a Causal Perceptron Network.Bayes net simulation.A simulation method based on the conditional Gaussian assumption.Implements the DAG-adaptation of the Onion (DaO) simulation method for generating linear data from a DAG, with exogenous errors drawn from one of the reference implementation's five variance-matched families (Gaussian by default; Exponential, Gumbel, Laplace, or Uniform via
daoErrorDistribution), as described in:Simulates data with the anatomy of a designed physical experiment (the archetype is the NASA Airfoil Self-Noise dataset), in contrast to an observational sample.Wrapper for the neural-net Generalized Additive Model (GAM) simulator.This class represents a Causal Perceptron Network.The GeneralSemSimulation class represents a simulation using a generalized structural equation model (SEM).This was used for a simulation to test the FTFC and FOFC algorithm and contains some carefully selected functions to test nonlinearity and non-Gaussianity.NL SEM simulation.This class represents a Simulation using Structural Equation Modeling (SEM).A version of the Lee and Hastic simulation.This class represents a continuous MNAR simulation.Linear Fisher Model.A simulation method based on the mixed variable polynomial assumption.A linear SEM simulation whose exogenous noises are drawn independently from the distribution given by the customNoiseExpression parameter (default Exp(1)) rather than from Gaussians.This class represents a nonlinear functions of linear simulation.Simulates data with the anatomy of a real observational scientific dataset (the archetype is the Algerian Forest Fires dataset, but with all complications defaulted off this is a plain mixed-data cross-sectional study).This class represents a post-nonlinear SEM model.This class represents a Simulation using Structural Equation Modeling (SEM).SEM the discretize.The interface that simulations must implement.A list of simulations to be compared.Jun 4, 2019 3:10:49 PMJun 4, 2019 5:21:45 PMASimulationimplementation that returns a single supplied data set.Standardized SEM simulation.Time series SEM simulation.Trained DAG model.