10,105 research outputs found
An efficient algorithm for computing interventional distributions in latent variable causal models
No full textProbabilistic inference in graphical models is the task of computing marginal and conditional densities of interest from a factorized representation of a joint probability distribution. Inference algorithms such as variable elimination and belief propagation take advantage of constraints embedded in this factorization to compute such densities efficiently. In this paper, we propose an algorithm which computes interventional distributions in latent variable causal models represented by acyclic directed mixed graphs (ADMGs). To compute these distributions efficiently, we take advantage of a recursive factorization which generalizes the usual Markov factorization for DAGs and the more recent factorization for ADMGs. Our algorithm can be viewed as a generalization of variable elimination to the mixed graph case. We show our algorithm is exponential in the mixed graph generalization of tree width
Private James Dem(m)ing leave of absence
No full textDocument written by Colonel Hiram Du Puy granting Private James Dem(m)ing of the 8th Ohio Volunteer Infantry a leave of absence from Camp Dennison, June 1861
Causal etiology of the research of James M. Robins
Get PDFThis issue of Statistical Science draws its inspiration from the work of James M. Robins. Jon Wellner, the Editor at the time, asked the two of us to edit a special issue that would highlight the research topics studied by Robins and the breadth and depth of Robins' contributions. Between the two of us, we have collaborated closely with Jamie for nearly 40 years. We agreed to edit this issue because we recognized that we were among the few in a position to relate the trajectory of his research career to date.Fil: Richardson, Thomas S.. University of Washington; Estados UnidosFil: Rotnitzky, Andrea Gloria. Universidad Torcuato Di Tella. Departamento de Economía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
Sparse nested Markov models with log-linear parameters
No full textHidden variables are ubiquitous in practical data analysis, and therefore modeling marginal densities and doing inference with the resulting models is an important problem in statistics, machine learning, and causal inference. Recently, a new type of graphical model, called the nested Markov model, was developed which captures equality constraints found in marginals of directed acyclic graph (DAG) models. Some of these constraints, such as the so called `Verma constraint', strictly generalize conditional independence. To make modeling and inference with nested Markov models practical, it is necessary to limit the number of parameters in the model, while still correctly capturing the constraints in the marginal of a DAG model. Placing such limits is similar in spirit to sparsity methods for undirected graphical models, and regression models. In this paper, we give a log-linear parameterization which allows sparse modeling with nested Markov models. We illustrate the advantages of this parameterization with a simulation study
The Limits of Causal Knowledge
No full textJames M. Robins, Richard Scheines, Peter Spirtes, and Larry Wasserman. The Limits of Causal Knowledge
ESTIMATION OF THE CAUSAL EFFECT OF A TIME-VARYING EXPOSURE ON THE MARGINAL MEAN OF A REPEATED BINARY OUTCOME
No full textWe provide sufficient conditions for estimating from
longitudinal data the causal effect of a time-dependent
exposure or treatment on the marginal probability of
response for a dichotomous outcome. We then show how one can
estimate this effect under these conditions using the g-
computation algorithm of Robins. We also derive the
conditions under which some current approaches to the
analysis of longitudinal data, such as the generalized
estimating equations (GEE) approach of Zeger and Liang, the
feedback model techniques of Liang and Zeger, and within-
subject conditional methods, can provide valid tests and
estimates of causal effects. We use our methods to estimate
the causal effect of maternal stress on the marginal
probability of a child's illness from the Mothers' Stress
and Children's Morbidity data and compare our results with
those previously obtained by Zeger and Liang using a GEE
approach
Mathematical Tracts Of the late Benjamin Robins ...
No full textPublished by James Wilson, M. D.Supralibros der Naturforschenden Gesellschaft in Zürich Exemplar der ZB ZürichHandschriftlicher Schenkungsvermerk auf dem fliegenden Blatt des ersten Bandes: "donné par Mylord Stanhope" Exemplar der ZB Züric
Polyphony and the anxiety of influence in the fiction of Henry James
Get PDFJames's fiction, especially in the Middle Phase, centres
on the figure of the artist and is characterized by, the two
interrelated aspects which previous criticism has largely
overlooked: the Bakhtinian 'polyphonic' -creation of
'author-thinkers'; and the conflict between ephebes and
precursors, for which Harold-Bloom's concept of 'the-anxiety of
influence' is the most illuminating model. Polyphony is the
narrative mode, and influence is the intra-artistic, theme.
These, as the Introduction to the thesis makes clear, are
rehearsed in James's inaugural novel, Roderick Hudson. Rowland
Mallet is an author-thinker, and his failure is caused by
authorial limitations. His monologism -is impaired by his
mistaking empathy for the authorial sympathy. Likewise,
Hudson's failure does not arise from a mercurial temperament,
but from a polyphonic shortcoming: not possessing the power of
fiction to contain the fiction of power in, his mentor. And the
relationships among the three artists - Gloriani, Hudson and
Singleton - perfectly exemplify the Bloomian-theme. It is these
two concepts, polyphony and influence, which are the major
preoccupation in the Middle Phase; as, the works chosen
demonstrate. These are a novella, a novel, and a number of
short stories all of which have been unjustifiably neglected.
Chapter One, on The Aspern Papers, argues that Tina Bordereau,
far from being, the artless victim seen by many critics,
actually challenges and defeats the narrator by the very form
of her narrative. Her 'realist' discourse undermines his
language of 'romance', and shows up its internal unstability.
Chapter Two is an extensive study of the critical reception of
The Tragic Muse. The most common areas of critical attention
have been its contemporary topicality, its relation to previous
novels on similar themes, and the possible genealogy of Gabriel
Nash. Those have all missed the core of the work. - Chapter Three
demonstrates how polyphony and the anxiety of influence make
the novel what it really is. Influence arises from the
juxtaposition of, and the wrestling between, artistic ephebes
and their precursors (Nick and Nash,, Miriam and Madame Carre).
The dialogic quality defined by Bakhtin is crucial to the
proper, and even-handed, characterization of all, the conflicts
in the novel. And since most of James's tales in the eighties
and nineties -are about 'masters - and acolytes, the anxiety of
influence remains central. Chapter Four is a study of 'The
Author of Beltraffiol' and 'The Lesson of the Master'. Again the
characters' manipulations are a crucial focus in a way that
G6rard Genette's terminology helps to illuminate. The fact that
the ephebe is the author-thinker emphasizes the inextricability
of the Bakhtinian and the Bloomian in James. Just as
polyphony offers a different focus for explicating the poetics
of James's fiction; so the ephebal conflict provides the basis
for a fresh perception of James's own artistic struggle
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