Calrk Glymour

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In an essay in this journal entitled "The Grand Leap' (Humphreys and Freedman [1996]) Paul Humphreys and David Freedman have offered a highly critical review of our book Causation, Prediction, and Search (Spirtes, Glymour, and Scheines [1993];' henceforth CPS). By omission and commission, their essay repeatedly and systematically misdescribes what we wrote,(More)
Three studies investigated whether young children make accurate causal inferences on the basis of patterns of variation and covariation. Children were presented with a new causal relation by means of a machine called the "blicket detector." Some objects, but not others, made the machine light up and play music. In the first 2 experiments, children were told(More)
We will respond to our commentators individually, but the order of our responses follows naturally from the issues they bring up. Judea Pearl describes SEM's unfortunate retreat from the clear causal semantics articulated by Sewall Wright (1921) and later by Haavelmo (1943) to the algebraic interpretation preferred more recently by econometricians. We agree(More)
The statistical community has brought logical rigor and mathematical precision to the problem of using data to make inferences about a model's parameter values. The TETRAD project, and related work in computer science and statistics, aims to apply those standards to the problem of using data and background knowledge to make inferences about a model's(More)
We describe a unification of old and recent ideas for formulating graphical models to explain time series data, including Granger causality, semi-automated search procedures for graphical causal models, modeling of contemporaneous influences in times series, and heuristic generalized additive model corrections to linear models. We illustrate the procedures(More)
The use of acycl ic , d i rec ted graphs (of ten ca l led 'DAG's) to s imul taneous ly represent causa l hypotheses and to encode independence and conditional independence constraints associated with those hypotheses has proved fruitful in the construction of expert systems, in the development of efficient updating algorithms (Pearl, 1988, Lauritzen et al.(More)
Scale-free networks (SFN) arise from simple growth processes, which can encourage efficient, centralized and fault tolerant communication (1). Recently its been shown that stable network hub structure is governed by a phase transition at exponents (>2.0) causing a dramatic change in network structure including a loss of global connectivity, an increasing(More)
Scale-free networks (SFN) arise from simple growth processes, which can encourage efficient, centralized and fault tolerant communication (1). Recently its been shown that stable network hub structure is governed by a phase transition at exponents (>2.0) causing a dramatic change in network structure including a loss of global connectivity, an increasing(More)
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