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Causal Graph
In statistics, econometrics, epidemiology, genetics and related disciplines, causal graphs (also known as path diagrams, causal Bayesian networks or DAGs) are probabilistic graphical models used to encode assumptions about the data-generating process. Causal graphs can be used for communication and for inference. As communication devices, the graphs provide formal and transparent representation of the causal assumptions that researchers may wish to convey and defend. As inference tools, the graphs enable researchers to estimate effect sizes from non-experimental data, derive testable implications of the assumptions encoded, test for external validity, and manage missing data and selection bias. Causal graphs were first used by the geneticist Sewall Wright under the rubric "path diagrams". They were later adopted by social scientists and, to a lesser extent, by economists. These models were initially confined to linear equations with fixed parameters. Modern developments have ex ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Path Analysis (statistics)
In statistics, path analysis is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple regression analysis, factor analysis, canonical correlation analysis, discriminant analysis, as well as more general families of models in the multivariate analysis of variance and covariance analyses (MANOVA, ANOVA, ANCOVA). In addition to being thought of as a form of multiple regression focusing on causality, path analysis can be viewed as a special case of structural equation modeling (SEM) – one in which only single indicators are employed for each of the variables in the causal model. That is, path analysis is SEM with a structural model, but no measurement model. Other terms used to refer to path analysis include causal modeling and analysis of covariance structures. Path analysis is considered by Judea Pearl to be a direct ancestor to the techniques of Causal inference. History Path analysis was developed a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Networks
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms can perform inference and learning in Bayesian networks. Bayesian networks that model sequences of variables (''e.g.'' speech signals or protein sequences) are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams. Graphical m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Directed Acyclic Graph
In mathematics, particularly graph theory, and computer science, a directed acyclic graph (DAG) is a directed graph with no directed cycles. That is, it consists of vertices and edges (also called ''arcs''), with each edge directed from one vertex to another, such that following those directions will never form a closed loop. A directed graph is a DAG if and only if it can be topologically ordered, by arranging the vertices as a linear ordering that is consistent with all edge directions. DAGs have numerous scientific and computational applications, ranging from biology (evolution, family trees, epidemiology) to information science (citation networks) to computation (scheduling). Directed acyclic graphs are sometimes instead called acyclic directed graphs or acyclic digraphs. Definitions A graph is formed by vertices and by edges connecting pairs of vertices, where the vertices can be any kind of object that is connected in pairs by edges. In the case of a directed graph ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graphical Models
''Graphical Models'' is an academic journal in computer graphics and geometry processing publisher by Elsevier. , its editor-in-chief is Jorg Peters of the University of Florida. History This journal has gone through multiple names. Founded in 1972 as ''Computer Graphics and Image Processing'' by Azriel Rosenfeld, it became the first journal to focus on computer image analysis. Its first change of name came in 1983, when it became ''Computer Vision, Graphics, and Image Processing''. In 1991 it split into two journals, ''CVGIP: Graphical Models and Image Processing'', and ''CVGIP: Image Understanding'', which later became ''Computer Vision and Image Understanding''. Meanwhile, in 1995, the journal ''Graphical Models and Image Processing'' removed the "CVGIP" prefix from its former name, and finally took its current title, ''Graphical Models'', in 2002. Ranking Although initially ranked by SCImago Journal Rank The SCImago Journal Rank (SJR) indicator is a measure of the prest ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Testable
Testability is a primary aspect of Science and the Scientific Method and is a property applying to an empirical hypothesis, involves two components: #Falsifiability or defeasibility, which means that counterexamples to the hypothesis are logically possible. #The practical feasibility of observing a reproducible series of such counterexamples if they do exist. In short, a hypothesis is testable if there is a possibility of deciding whether it is true or false based on experimentation by anyone. This allows anyone to decide whether a theory can be supported or refuted by data. However, the interpretation of experimental data may be also inconclusive or uncertain. Karl Popper introduced the concept that scientific knowledge had the property of Falsifiability.as published in '' The Logic of Scientific Discovery.Karl Popper "The Logic of Scientific Discovery", 1934 (as Logik der Forschung, English translation 1959)'', ISBN 0415278449 and 2002 ISBN 9780415278447, 0415278449 See als ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sewall Wright
Sewall Green Wright FRS(For) Honorary FRSE (December 21, 1889March 3, 1988) was an American geneticist known for his influential work on evolutionary theory and also for his work on path analysis. He was a founder of population genetics alongside Ronald Fisher and J. B. S. Haldane, which was a major step in the development of the modern synthesis combining genetics with evolution. He discovered the inbreeding coefficient and methods of computing it in pedigree animals. He extended this work to populations, computing the amount of inbreeding between members of populations as a result of random genetic drift, and along with Fisher he pioneered methods for computing the distribution of gene frequencies among populations as a result of the interaction of natural selection, mutation, migration and genetic drift. Wright also made major contributions to mammalian and biochemical genetics. Biography Sewall Wright was born in Melrose, Massachusetts to Philip Green Wright and Elizabet ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Network
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms can perform inference and learning in Bayesian networks. Bayesian networks that model sequences of variables (''e.g.'' speech signals or protein sequences) are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams. Graphical m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Structural Equation Model
Structural equation modeling (SEM) is a label for a diverse set of methods used by scientists in both experimental and observational research across the sciences, business, and other fields. It is used most in the social and behavioral sciences. A definition of SEM is difficult without reference to highly technical language, but a good starting place is the name itself. SEM involves the construction of a ''model'', to represent how various aspects of an observable or theoretical phenomenon are thought to be Causality, causally structurally related to one another. The ''structure, structural'' aspect of the model implies theoretical associations between variables that represent the phenomenon under investigation. The postulated causal structuring is often depicted with arrows representing causal connections between variables (as in Figures 1 and 2) but these causal connections can be equivalently represented as equations. The causal structures imply that specific patterns of co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
College NotID
A college (Latin: ''collegium'') is an educational institution or a constituent part of one. A college may be a degree-awarding tertiary educational institution, a part of a collegiate or federal university, an institution offering vocational education, or a secondary school. In most of the world, a college may be a high school or secondary school, a college of further education, a training institution that awards trade qualifications, a higher-education provider that does not have university status (often without its own degree-awarding powers), or a constituent part of a university. In the United States, a college may offer undergraduate programs – either as an independent institution or as the undergraduate program of a university – or it may be a residential college of a university or a community college, referring to (primarily public) higher education institutions that aim to provide affordable and accessible education, usually limited to two-year assoc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
College NotID Proj
A college (Latin: ''collegium'') is an educational institution or a constituent part of one. A college may be a degree-awarding tertiary educational institution, a part of a collegiate or federal university, an institution offering vocational education, or a secondary school. In most of the world, a college may be a high school or secondary school, a college of further education, a training institution that awards trade qualifications, a higher-education provider that does not have university status (often without its own degree-awarding powers), or a constituent part of a university. In the United States, a college may offer undergraduate programs – either as an independent institution or as the undergraduate program of a university – or it may be a residential college of a university or a community college, referring to (primarily public) higher education institutions that aim to provide affordable and accessible education, usually limited to two-year ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
College
A college (Latin: ''collegium'') is an educational institution or a constituent part of one. A college may be a degree-awarding tertiary educational institution, a part of a collegiate or federal university, an institution offering vocational education, or a secondary school. In most of the world, a college may be a high school or secondary school, a college of further education, a training institution that awards trade qualifications, a higher-education provider that does not have university status (often without its own degree-awarding powers), or a constituent part of a university. In the United States, a college may offer undergraduate programs – either as an independent institution or as the undergraduate program of a university – or it may be a residential college of a university or a community college, referring to (primarily public) higher education institutions that aim to provide affordable and accessible education, usually limited to two-year ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
College Proj
A college (Latin: ''collegium'') is an educational institution or a University system, constituent part of one. A college may be a academic degree, degree-awarding Tertiary education, tertiary educational institution, a part of a collegiate university, collegiate or federal university, an institution offering vocational education, or a secondary school. In most of the world, a college may be a high school or secondary school, a college of further education, a training institution that awards trade qualifications, a higher-education provider that does not have university status (often without its own degree-awarding powers), or a constituent part of a university. In the United States, a college may offer undergraduate education, undergraduate programs – either as an independent institution or as the undergraduate program of a university – or it may be a residential college of a university or a Community colleges in the United States, community college, referring ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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