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cff-version: 1.2.0
message: 'To cite package "rcausim" in publications use:'
type: software
license: GPL-3.0-only
title: 'rcausim: Generate Causally-Simulated Data'
version: 0.1.1
doi: 10.32614/CRAN.package.rcausim
abstract: Generate causally-simulated data to serve as ground truth for evaluating
  methods in causal discovery and effect estimation. The package provides tools to
  assist in defining functions based on specified edges, and conversely, defining
  edges based on functions. It enables the generation of data according to these predefined
  functions and causal structures. This is particularly useful for researchers in
  fields such as artificial intelligence, statistics, biology, medicine, epidemiology,
  economics, and social sciences, who are developing a general or a domain-specific
  methods to discover causal structures and estimate causal effects. Data simulation
  adheres to principles of structural causal modeling. Detailed methodologies and
  examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rcausim/blob/master/doc/causal_simulation_exemplar.html>.
authors:
- family-names: Sufriyana
  given-names: Herdiantri
  email: herdi@tmu.edu.tw
  orcid: https://orcid.org/0000-0001-9178-0222
- family-names: Su
  given-names: Emily Chia-Yu
  email: emily@tmu.edu.tw
  orcid: https://orcid.org/0000-0003-4801-5159
repository: https://CRAN.R-project.org/package=rcausim
date-released: '2024-06-24'
contact:
- family-names: Sufriyana
  given-names: Herdiantri
  email: herdi@tmu.edu.tw
  orcid: https://orcid.org/0000-0001-9178-0222