• TETRAD

  • Referenced in 399 articles [sw12177]
  • predicts with, and searches for causal and statistical models. The aim of the program...
  • MIM

  • Referenced in 129 articles [sw26139]
  • dependencies, both associational and causal, between the variables in the model. This textbook provides ... variables. Further chapters cover hypothesis testing and model selection. Chapters ... causal inference, relevant when graphical models are given a causal interpretation. This book will provide...
  • vars

  • Referenced in 32 articles [sw04507]
  • package vars: VAR Modelling , Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance...
  • DirectLiNGAM

  • Referenced in 16 articles [sw15504]
  • Structural equation models and Bayesian networks have been widely used to analyze causal relations between ... structure of a linear acyclic model, that is, a causal ordering of variables and their ... direct method to estimate a causal ordering and connection strengths based on non-Gaussianity ... steps if the data strictly follows the model, that is, if all the model assumptions...
  • causaleffect

  • Referenced in 5 articles [sw11067]
  • Expressions of Joint Interventional Distributions in Causal Models. An implementation of the complete identification algorithm ... expressions of joint interventional distributions in causal models, which contain unobserved variables and induce directed...
  • VipTool

  • Referenced in 14 articles [sw13755]
  • project is to establish a simulation and modelling concept for business processes given by Petri ... bundle of methods concerned with causality and concurrency modelled by partially ordered runs of p/t-nets...
  • CreditRisk+

  • Referenced in 43 articles [sw31697]
  • causes of market price movements. The CREDITRISK+ Model considers default rates as continuous random variables ... correlated, even though there is no causal link between them. The effects of these background ... factors are incorporated into the CREDITRISK+ Model through the use of default rate volatilities...
  • dagitty

  • Referenced in 4 articles [sw16593]
  • dagitty.net>, for analyzing structural causal models (also known as directed acyclic graphs or DAGs ... package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications ... separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation...
  • MatchIt

  • Referenced in 13 articles [sw10538]
  • MatchIt: Nonparametric Preprocessing for Parametric Causal Inference. MatchIt implements the suggestions of Ho, Imai, King ... Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt ... dependence of causal inferences on hard-to-justify, but commonly made, statistical modeling assumptions...
  • mediation

  • Referenced in 13 articles [sw04536]
  • addition to the estimation of causal mediation effects, the software also allows researchers to conduct ... sensitivity analysis for certain parametric models...
  • CAM

  • Referenced in 2 articles [sw23430]
  • package CAM: Causal Additive Model (CAM) .The code takes an n x p data matrix ... fits a Causal Additive Model (CAM) for estimating the causal structure of the underlying process ... Bühlmann, J. Peters, J. Ernest: ”CAM: Causal Additive Models, high-dimensional order search and penalized...
  • SCTL-MUS

  • Referenced in 8 articles [sw02245]
  • order to formalise this model, a multi-valued causal temporal logic, referred to as Simple ... Causal Temporal Logic (SCTL), is defined for the acquisition and specification of the functional requirements ... Model of Unspecified States (MUS) is also defined with a double goal: firstly, to show...
  • Horus

  • Referenced in 15 articles [sw21811]
  • group communications model providing (among others) unreliable or reliable FIFO, causal, or total group multicasts...
  • JCI

  • Referenced in 2 articles [sw35495]
  • unifies both approaches. JCI is a causal modeling framework rather than a specific algorithm...
  • CAnoVa

  • Referenced in 1 article [sw34658]
  • CAnoVa. A software for causal modeling. The new impulse given in the last decade ... theory of individual and average causal effects is mostly due to the approach developed ... present CAnoVa, a software for causal modeling that allows a straightforward use of these ... allows to test for confounding and for causal effects even in case of designs with...
  • gma

  • Referenced in 2 articles [sw26339]
  • model for the time series of a single participant performs the causal mediation analysis ... which integrates the structural equation modeling and the Granger causality frameworks. A vector autoregressive model...
  • SCRalyze

  • Referenced in 1 article [sw39503]
  • using linear convolution models and dynamic causal modelling. A flexible import interface and many utilities...
  • semibart

  • Referenced in 1 article [sw31324]
  • result is a Bayesian semiparametric linear regression model where the posterior distribution of the parameters ... example of this occurs in causal modeling with the structural mean model (SMM). Under certain...
  • wfe

  • Referenced in 1 article [sw23425]
  • Weighted Linear Fixed Effects Regression Models for Causal Inference. Provides a computationally efficient ... fitting weighted linear fixed effects estimators for causal inference with various weighting schemes. Weighted linear ... Linear Fixed Effects Regression Models for Causal Inference with Longitudinal Data?”, available at
  • DoWhy

  • Referenced in 1 article [sw36878]
  • causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based ... unified language for causal inference, combining causal graphical models and potential outcomes frameworks...