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Directed graph that models causal relationships between variables
epidemiology, genetics and related disciplines, causal graphs (also known as path diagrams, causal Bayesian networks or DAGs) are probabilistic graphical
Causal_graph
Directed graph with no directed cycles
In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it
Directed_acyclic_graph
Method of identifying the fundamental causes of faults or problems
Distinguish between the root-cause and other causal factors (e.g., via event correlation) Establish a causal graph between the root-cause and the problem.
Root-cause_analysis
How one process influences another
of measurement. While derivations in causal calculus rely on the structure of the causal graph, parts of the causal structure can, under certain assumptions
Causality
Branch of statistics
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main
Causal_inference
Mathematical framework for identifying causal effects
to determine whether causal effects can be identified from observational data under specific assumptions encoded in a causal graph. It provides a systematic
Do-calculus
Type of flowchart
Acyclic Graphs (DAGs). However the phrase “causal map” is usually reserved for qualitative or merely semi-quantitative maps. In this sense, causal maps can
Causal_map
Variable that is causally influenced by two or more variables
In statistics and causal graphs, a variable is a collider when it is causally influenced by two or more variables. The name "collider" reflects the fact
Collider_(statistics)
Area of discrete mathematics
computer science, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. A graph in this context
Graph_theory
Visualization of variable interrelationships
A causal loop diagram (CLD) is a causal diagram that visualizes how different variables in a system are causally interrelated. The diagram consists of
Causal_loop_diagram
Conceptual model in philosophy of science
Causal models often employ formal causal notation, such as structural equation modeling or causal directed acyclic graphs (DAGs), to describe relationships
Causal_model
independence model. In the context of causal inference, ancestral graphs assume the Causal Markov Condition (CMC) and Causal Faithfulness Condition (CFC). The
Ancestral_graph
Graphical representation of energy flows in physical systems
on the bond graph itself using the causal stroke notation. A causal bond graph can be put into state-space form if: every bond has a causal stroke and
Bond_graph
Technique in statistics
quasi-experimental method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment
Instrumental_variables
Probabilistic graphical representation of causal relationships
conditional dependencies via a directed acyclic graph (DAG). While it is one of several forms of causal notation, causal networks are special cases of Bayesian
Bayesian_network
if releasing one's fingers from a hammer always causes it to fall. A causal graph could be created to acknowledge that both the presence of gravity and
Causal_Markov_condition
Method for accident analysis to determine causal relationships
analysis is a why–because graph (WBG), a type of causal notation used to represent interdependencies within a system and depict causal relations between factors
Why–because_analysis
Field of statistics
Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. Typically it involves establishing four
Causal_analysis
Term used in machine learning
apparently only be faithfully described using an overwhelmingly large causal graph." They also found that the model includes "mechanisms that could underlie
Stochastic_parrot
Bias in causal inference
associations. Several notation systems and formal frameworks, such as causal directed acyclic graphs (DAGs), have been developed to represent and detect confounding
Confounding
Notation to express cause and effect
other symbols. Causal notation is notation used to express cause and effect. In nature and human societies, many phenomena have causal relationships where
Causal_notation
Model in software programming
representations for the causal context meta-data. One is to maintain an explicit dependency graph of the causal dependence relation. Because such a graph can grow arbitrarily
Causal_consistency
Method of statistical analysis
The Rubin causal model (RCM), also known as the Neyman–Rubin causal model, is an approach to the statistical analysis of cause and effect based on the
Rubin_causal_model
Interpretable computational sub-graphs within artificial neural networks
apparently only be faithfully described using an overwhelmingly large causal graph." Includes "mechanisms that could underlie a simple form of metacognition"
Circuit_(neural_network)
Undirected, connected, and acyclic graph
In graph theory, a tree is an undirected graph in which every pair of distinct vertices is connected by exactly one path, or equivalently, a connected
Tree_(graph_theory)
Measurement of algorithmic bias
framework to deal with causal analysis of fairness. They suggest the use of a Standard Fairness Model, consisting of a causal graph with 4 types of variables:
Fairness_(machine_learning)
Assigning directions to the edges of an undirected graph
In graph theory, an orientation of an undirected graph is an assignment of a direction to each edge, turning the initial graph into a directed graph. A
Orientation_(graph_theory)
American geneticist (1889–1988)
acceptance by several technical disciplines (specifically statistics and formal causal analysis). OpenMx has as its icon a representation of Wright's piebald guinea
Sewall_Wright
causal links on the basis of highlighted passages of source text cauzality.com compendiuminstitute.org dagitty.net banxia.com "GraphCommons". "GraphCommons
List of causal mapping software
List_of_causal_mapping_software
Graph with directed and undirected edges
In graph theory, a mixed graph G = (V, E, A) is a graph consisting of a set of vertices V, a set of (undirected) edges E, and a set of directed edges (or
Mixed_graph
Field in statistics pertaining to establishing cause and effect
Causal analysis is the field of experimental design and statistical analysis pertaining to establishing cause and effect. Exploratory causal analysis (ECA)
Exploratory_causal_analysis
Type of graph in mathematics
specifically in graph theory, a polytree (also called directed tree, oriented tree or singly connected network) is a directed acyclic graph whose underlying
Polytree
American sociologist (born 1971)
diagnostic routines for detecting heterogeneity in causal effect estimates and applications of the causal graph methodology, including applications to the tradition
Stephen_L._Morgan
Greek physicist (born 1971)
the random dynamics of the graph under the influence of quantum fluctuations and temperature. At high temperature the graph is in Phase I where all the
Fotini_Markopoulou-Kalamara
Study of circular causal processes
Cybernetics is the transdisciplinary study of circular causal processes such as feedback and recursion, where the outcomes of actions return as inputs
Cybernetics
Error in statistical reasoning with groups
frequency data are unduly given causal interpretations. The paradox can be resolved when confounding variables and causal relations are appropriately addressed
Simpson's_paradox
Flow graph invented by Claude Shannon
A signal-flow graph or signal-flowgraph (SFG), invented by Claude Shannon, but often called a Mason graph after Samuel Jefferson Mason who coined the
Signal-flow_graph
2000 book by Judea Pearl
Introduction to Probabilities, Graphs, and Causal Models A Theory of Inferred Causation Causal Diagrams and the Identification of Causal Effects Actions, Plans
Causality_(book)
Heinze, Rieke (July 2020). "Cold-pool-driven convective initiation: using causal graph analysis to determine what convection-permitting models are missing"
Cold_pool
Graph with sign-labeled edges
In the area of graph theory in mathematics, a signed graph is a graph in which each edge has a positive or negative sign. A signed graph is balanced if
Signed_graph
Structure from which the geometry of the universe arises
undergo quantum fluctuations. Causal sets by Bombelli, Lee, Meyer and Sorkin All of spacetime at very small scales is a causal set consisting of locally finite
Pregeometry_(physics)
Process where information about current status is used to influence future status
cause-and-effect has to be handled carefully when applied to feedback systems: Simple causal reasoning about a feedback system is difficult because the first system
Feedback
Concept in machine learning
problem of disentangling the causal factors based on second order or higher order statistics associated with each causal factor. Tensor (multilinear)
Tensor_(machine_learning)
Form of causal modeling that fit networks of constructs to data
observed). Additional causal connections link those latent variables to observed variables whose values appear in a data set. The causal connections are represented
Structural_equation_modeling
Study of non-linear complex systems
political system or mechanical system) may be represented as a causal loop diagram. A causal loop diagram is a simple map of a system with all its constituent
System_dynamics
Statistical matching technique
Parametric Causal Inference". Political Analysis. 15 (3): 199–236. doi:10.1093/pan/mpl013. "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference"
Propensity_score_matching
relationships in a graph structure that draws inspiration from physics. Just as physical reality is described through spacetime coordinates and causal relationships
Semantic_spacetime
Algorithm for statistical inference on graphical models
We describe here the variant that operates on a factor graph. A factor graph is a bipartite graph containing nodes corresponding to variables V {\displaystyle
Belief_propagation
Topics referred to by the same term
the minimization of states in a state machine Implication graph, a skew-symmetric directed graph used for analyzing complex Boolean expressions Implication
Implication
Process in algebra
notations and operations that are widely used in the field. A multi-way graph with K perspectives is a collection of K matrices X 1 , X 2 . . . . . X
Tensor_decomposition
Algorithm for modelling sequential data
transformer architectures over long inputs. The standard attention graph is either all-to-all or causal, both of which scales as O ( N 2 ) {\displaystyle O(N^{2})}
Transformer_(deep_learning)
Statistical term
the directed graph of the model must contain no cycles, i.e. it is a directed acyclic graph, which has been extensively studied in the causal analysis framework
Path_analysis_(statistics)
operational awareness or external causal relationships. Recent developments in big data analysis, combined with graph mining techniques, make it possible
Enterprise_social_graph
Set of statistical processes for estimating the relationships among variables
between two variables has a causal interpretation. The latter is especially important when researchers hope to estimate causal relationships using observational
Regression_analysis
Chinese computer scientist
on Data Mining (SDM), pp. 675–683, 2018. Translating literature into causal graphs: toward automated experiment selection, by Nicholas Matiasz, Justin
Wei_Wang_(computer_scientist)
Social structure made up of a set of social actors
field which emerged from social psychology, sociology, statistics, and graph theory. Georg Simmel authored early structural theories in sociology emphasizing
Social_network
Subset of variables that contains all the useful information
whether it be physical or causal. Andrey Markov Free energy minimisation Moral graph Separation of concerns Causality Causal inference Pearl, Judea (1988)
Markov_blanket
Statistical method in genetic epidemiology
abbreviated to MR) is a method using measured variation in genes to examine the causal effect of an exposure on an outcome. Under key assumptions (see below),
Mendelian_randomization
Experiment using randomness in some aspect, usually to aid in removal of bias
Rubin Causal Model provides a common way to describe a randomized experiment. While the Rubin Causal Model provides a framework for defining the causal parameters
Randomized_experiment
Set of spacetime events, light-connected to a given event
and if the growing circle with the vertical axis representing time is graphed, the result is a cone, known as the future light cone. The past light cone
Light_cone
Idea in quantum gravity
"quantum graphity" proposal of Konopka, Markopoulu-Kalamara, Severini and Smolin, the fundamental degrees of freedom exist on a dynamical graph that is
Induced_gravity
Statistical relationship
presence of a correlation is not sufficient to infer the presence of a causal relationship (i.e., correlation does not imply causation). Furthermore,
Correlation
Extent to which the results of a study can be generalized
those where external validity is theoretically impossible. Using graph-based causal inference calculus, they derived a necessary and sufficient condition
External_validity
World line of a particle in spacetime which returns to its starting point
event horizons excised would still be causally well behaved and an observer might not be able to detect the causal violation. When discussing the evolution
Closed_timelike_curve
Probabilistic model
or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables
Graphical_model
Class of statistical models
Thwaites, Peter; Smith, Jim Q.; Riccomagno, Eva (2010). "Causal analysis with chain event graphs". Artificial Intelligence. 174 (12–13): 889–909. doi:10
Staged_tree_(mathematics)
Terms to describe a conditional relationship between two statements
condition. In data analytics, necessity and sufficiency can refer to different causal logics, where necessary condition analysis and qualitative comparative analysis
Necessity_and_sufficiency
Chinese mathematician (born 1968)
vision and intelligence, which includes the Spatial, Temporal, and Causal And-Or graph (STC-AOG) as a unified representation and numerous Monte Carlo methods
Song-Chun_Zhu
View that mind is a ubiquitous feature of reality
it to exert any causal power on the world (a state of affairs philosophers call epiphenomenalism). If consciousness plays no causal role, then it is
Panpsychism
Information-theoretical limit on transmission rate in a communication channel
and the channel outputs, where the maximization is with respect to the causal conditioning of the input given the output. The directed information was
Channel_capacity
Model in development economics
the help of the graph on the right, which is an integration of the industrial sector graph with an inverted agricultural sector graph, such that the origin
Fei–Ranis model of economic growth
Fei–Ranis_model_of_economic_growth
Unpredictable phenomenon in complex systems
supervenient downward causal power arise, since by definition it cannot be due to the aggregation of the micro-level potentialities? Such causal powers would be
Emergence
Decision support tool
with the target variable on the right. They can also denote temporal or causal relations. Commonly a decision tree is drawn using flowchart symbols as
Decision_tree
Hypothetical faster-than-light particle
since tachyons are confined to the spacelike portion of the energy–momentum graph, they cannot slow down to subluminal (slower-than-light) speeds. In a Lorentz
Tachyon
Cycles going through a hierarchy
themselves that they are provable", but they don't exhibit the sort of downward causal powers described in the displayed quote. Hofstadter points to Bach's Canon
Strange_loop
Method in electronic engineering
(MGF) is a method for finding the transfer function of a linear signal-flow graph (SFG). The formula was derived by Samuel Jefferson Mason, for whom it is
Mason's_gain_formula
Overview of democracy measures
democracy indices / rankings enables data analytical approaches for studying causal mechanisms of regime transformation processes. Democracy indices / rankings
Democracy_indices
Topics referred to by the same term
directly optimize a model Feedback arc set, in graph theory, a method of eliminating directed graphs Feedback vertex set, in computational complexity
Feedback_(disambiguation)
Method of analysis for systems of interacting components
intentions to one another in the form of promises. Promise theory is grounded in graph theory and set theory. The goal of promise theory is to reveal the behavior
Promise_theory
American epidemiologist
mediation analysis along with the book, Explanation in Causal Inference, on the topic. His work on causal inference is grounded in the potential outcomes framework
Tyler_VanderWeele
Causal or moderating relationship between statistical variables
a situation in which the effect of one causal variable on an outcome depends on the state of a second causal variable (that is, when effects of the two
Interaction_(statistics)
System with multiple networked computers
different kinds of network graphs, such as undirected rings, unidirectional rings, complete graphs, grids, directed Euler graphs, and others. A general method
Distributed_computing
Expression of a function as the composition of two functions
Interaction (statistics)(a situation in which one causal variable depends on the state of a second causal variable)[clarification needed] between the components
Functional_decomposition
Method for estimating new data outside known data points
created the existing data points. Some experts have proposed the use of causal forces in the evaluation of extrapolation methods. Crucial questions are
Extrapolation
Set of constraints conceptualised as a border
Supply graph
Margin_(economics)
Hypothetical physical concept
theories is given in the following graph, where each unification step leads one level up on the graph. In this graph, electroweak unification occurs at
Theory_of_everything
Graphoid math statements
independence in probability theory is shared by undirected graphs. Variables are represented as nodes in a graph in such a way that variable sets X and Y are independent
Graphoid
Statistical technique to use observational data for causal analysis
group, γ s {\displaystyle \gamma _{s}} is the vertical intercept for the graph for s {\displaystyle s} , and λ t {\displaystyle \lambda _{t}} is the time
Difference_in_differences
Norwegian–Swedish statistician, economist (1908–1992)
methods of partial least squares (PLS) and graphical models. Wold's work on causal inference from observational studies was decades ahead of its time, according
Herman_Wold
Ways how entities stand to each other
substantial contents. Logical relations are relations between propositions while causal relations connect concrete events. Symmetric, transitive, and reflexive
Relation_(philosophy)
Account that presents connected events
and compare the structures (expressed as "and" in a directed graph where multiple causal links incident into a node are conjoined) of action-driven sequential
Narrative
capacity of networks with in-block memory, gambling with causal side information, compression with causal side information, real-time control communication settings
Directed_information
Machine learning technique
w_{ij}=0} for all i < j {\displaystyle i<j} , called "causal masking". This attention mechanism is the "causally masked self-attention". Recurrent neural network
Attention_(machine_learning)
Combination of electronics and mechanics
theory – Branch of engineering and mathematics Cybernetics – Study of circular causal processes Ecomechatronics – Mechatronical technology reducing the ecological
Mechatronics
Event that is closest to, or immediately responsible for causing, some observed result
cause, which acts less directly through the proximate cause. In formal causal inference, the proximate cause is called a mediator. Example: Why did the
Proximate and ultimate causation
Proximate_and_ultimate_causation
Form of engineering diagram
Causal Logic Nets has been presented in. In order to capture concurrency and choice in compact form, a model called Conditional Partial Order Graph (CPOG)
Signal_transition_graphs
American epidemiologist
epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials, particularly
James_Robins
Filter whose phase response is proportional to frequency
filter twice, the second time with time reversed. (For a causal filter, this second pass is anti-causal, so using this approach in real time has not been shown
Linear_phase
Mathematical set with an ordering
families of orderings than posets Causal set, a poset-based approach to quantum gravity Comparability graph – Graph linking pairs of comparable elements
Partially_ordered_set
Competitive algorithm for searching a problem space
better performance, solving sudoku puzzles, hyperparameter optimization, and causal inference. In a genetic algorithm, a population of candidate solutions (called
Genetic_algorithm
CAUSAL GRAPH
CAUSAL GRAPH
Male
Irish
Variant spelling of Irish Gaelic Cathal, CAHAL means "battle ruler."
Surname or Lastname
English (of Norman origin)
English (of Norman origin) : topographic name for someone who lived by a causeway, Middle English caucey (from Old Norman French cauciée); the ending of the word was in time assimilated by folk etymology to Middle English way.
Boy/Male
Indian
Decisive
Boy/Male
Muslim
Pure water
Boy/Male
Hindu
Happy
Boy/Male
Arabic
Stubborn.
Boy/Male
Hindu
God is gracious, Swan like
Boy/Male
Indian
Decisive
Female
Swedish
Variant spelling of Swedish Kajsa, CAJSA means "pure."
Surname or Lastname
English
English : perhaps a variant spelling of Cosby.
Surname or Lastname
English (West Midlands)
English (West Midlands) : probably an occupational name for a maker of leggings or other apparel for the legs or feet, from an agent derivative probably of a northern variant of Old French chausse ‘footwear’ or ‘leggings’ (see Chausse).
Boy/Male
Indian
Casual
Boy/Male
Irish
From Cashel.
Surname or Lastname
English (of Norman origin)
English (of Norman origin) : habitational name for someone from Cassel in Nord, France.English : variant spelling of Castle.Americanized or older spelling of German Kassel.
Boy/Male
Hindu
Happy
Boy/Male
Celtic Irish
Strong in battle.
Boy/Male
Irish
Powerful warrior.
Surname or Lastname
English
English : variant spelling of Carnell.French : metonymic occupational name for a maker of latches and hinges, from Old Picard carnel, Old French charnel ‘hinge’.
Boy/Male
Hindu
Lover or joyful or glad
Boy/Male
Danish Swedish American Latin Shakespearean
Long hair.
CAUSAL GRAPH
CAUSAL GRAPH
Girl/Female
American, Australian, British, English
God is My Oath; Abbreviation of Eleanor and Ellen
Surname or Lastname
Irish
Irish : shortened form of O’Hanley, an Anglicized form of Gaelic Ó hÃinle ‘descendant of Ãinle’, a personal name meaning ‘champion’. This is the name of a ruling family in Connacht; it is now common in southern Ireland.English : habitational name from any of various places, such as Handley in Cheshire, Derbyshire. Northamptonshire, and Dorset and Hanley in Staffordshire and Worcestershire, all from Old English hÄ“an, the weak dative case (originally used after a preposition and article) of hÄ“ah ‘high’ + lÄ“ah ‘wood’, ‘clearing’, or from Handley Farm in Clayhanger, Devon, which is named from Old English hÄn ‘(boundary) stone’ + lÄ“ah.
Boy/Male
Tamil
Santvan | ஸாஂதà¯à®µà®¨
Consolation
Boy/Male
Tamil
Srivathsan | ஸà¯à®°à¯€à®µà®¾à®¤à¯à®¸à®¨
Brilliant, Lord venkateswara
Girl/Female
Indian, Tamil
Good Character
Male
Dutch
, awful or venerable one.
Boy/Male
Hindu, Indian
Lord Vishnu
Boy/Male
Hindu, Indian, Marathi
Ancient Hindu Warrior
Boy/Male
American, Australian, British, Christian, Danish, English, German, Norwegian, Scandinavian, Swedish
Powerful Army; Strong Counselor; From the Ancient Personal Name Ragnar; Wise Army; Wise Warrior
Boy/Male
Irish
Triumphant.
CAUSAL GRAPH
CAUSAL GRAPH
CAUSAL GRAPH
CAUSAL GRAPH
CAUSAL GRAPH
a.
Of or pertaining to the thigh or leg, or to any of the parts called crura; as, the crural arteries; crural arch; crural canal; crural ring.
a.
Capable of being caused.
a.
Having the form of a caecum, or bag with one opening; baglike; as, the caecal extremity of a duct.
a.
Coming without regularity; occasional; incidental; as, casual expenses.
n.
A tube or duct; as, the alimentary canal; the semicircular canals of the ear.
v.
That which is the occasion of an action or state; ground; reason; motive; as, cause for rejoicing.
imp. & p. p.
of Cause
a.
Of or pertaining to case; as, a casal ending.
a.
Relating to a cause or causes; inplying or containing a cause or causes; expressing a cause; causative.
a.
Resembling a vassal; slavish; servile.
a.
Having a quality imparted by means of the nose; and specifically, made by lowering the soft palate, in some cases with closure of the oral passage, the voice thus issuing (wholly or partially) through the nose, as in the consonants m, n, ng (see Guide to Pronunciation, // 20, 208); characterized by resonance in the nasal passage; as, a nasal vowel; a nasal utterance.
n.
A Roman emperor, as being the successor of Augustus Caesar. Hence, a kaiser, or emperor of Germany, or any emperor or powerful ruler. See Kaiser, Kesar.
n.
One of the nasal bones.
n.
A tarsal bone or cartilage; a tarsale.
a.
Of or pertaining to the ear; as, aural medicine and surgery.
v. t.
To treat as a vassal; to subject to control; to enslave.
n.
A causal word or form of speech.
n.
One who or that which causes.
v. i.
To assign or show cause; to give a reason; to make excuse.
adv.
According to the order or series of causes; by tracing effects to causes.