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6,062
Principal Curves
, 1989
"... Principal curves are smooth onedimensional curves that pass through the middle of a pdimensional data set, providing a nonlinear summary of the data. They are nonparametric, and their shape is suggested by the data. The algorithm for constructing principal curve starts with some prior summary, suc ..."
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Cited by 394 (1 self)
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curves are defined, an algorithm for their construction is given, some theoretical results are presented, and the procedure is compared to other generalizations of principal components. Two applications illustrate the use of principal curves. The first describes how the principalcurve procedure was used
Evaluating Interval Forecasts
 International Economic Review
, 1997
"... This paper is intended to address the deficiency by clearly defining what is meant by a "good" interval forecast, and describing how to test if a given interval forecast deserves the label "good". One of the motivations of Engle's (1982) classic paper was to form dynamic int ..."
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Cited by 364 (11 self)
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This paper is intended to address the deficiency by clearly defining what is meant by a "good" interval forecast, and describing how to test if a given interval forecast deserves the label "good". One of the motivations of Engle's (1982) classic paper was to form dynamic
A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments
, 2000
"... We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider recent Bayesian approaches developed by Chao and Phillips (1998, CP), Geweke (1996), Kleibergen a ..."
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Cited by 8 (0 self)
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We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider recent Bayesian approaches developed by Chao and Phillips (1998, CP), Geweke (1996), Kleibergen
Sampling signals with finite rate of innovation
 IEEE Transactions on Signal Processing
, 2002
"... Abstractâ€”Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate of innovation. Examples of signals with a finite rate of innovation include streams of Diracs (e.g., the Poisson process), nonuniform splines, and piecewise polynomials ..."
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Cited by 350 (67 self)
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polynomials. Even though these signals are not bandlimited, we show that they can be sampled uniformly at (or above) the rate of innovation using an appropriate kernel and then be perfectly reconstructed. Thus, we prove sampling theorems for classes of signals and kernels that generalize the classic
A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli
 Psychological Review
, 1980
"... Several formal models of excitatory classical conditioning are reviewed. It is suggested that a central problem for all of them is the explanation of cases in which learning does not occur in spite of the fact that the conditioned stimulus is a signal for the reinforcer. We propose a new model that ..."
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Cited by 290 (11 self)
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Several formal models of excitatory classical conditioning are reviewed. It is suggested that a central problem for all of them is the explanation of cases in which learning does not occur in spite of the fact that the conditioned stimulus is a signal for the reinforcer. We propose a new model
Classical and Bayesian inference in neuroimaging: Theory
 NeuroImage
, 2002
"... This paper reviews hierarchical observation models, used in functional neuroimaging, in a Bayesian light. It emphasizes the common ground shared by classical and Bayesian methods to show that conventional analyses of neuroimaging data can be usefully extended within an empirical Bayesian framework. ..."
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Cited by 173 (42 self)
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. In particular we formulate the procedures used in conventional data analysis in terms of hierarchical linear models and establish a connection between classical inference and parametric empirical Bayes (PEB) through covariance component estimation. This estimation is based on an expectation maximization or EM
Realtime logics: complexity and expressiveness
 INFORMATION AND COMPUTATION
, 1993
"... The theory of the natural numbers with linear order and monadic predicates underlies propositional linear temporal logic. To study temporal logics that are suitable for reasoning about realtime systems, we combine this classical theory of in nite state sequences with a theory of discrete time, via ..."
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Cited by 252 (16 self)
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The theory of the natural numbers with linear order and monadic predicates underlies propositional linear temporal logic. To study temporal logics that are suitable for reasoning about realtime systems, we combine this classical theory of in nite state sequences with a theory of discrete time, via
PCLASSIC: A tractable probabilistic description logic
 In Proceedings of AAAI97
, 1997
"... Knowledge representation languages invariably reflect a tradeoff between expressivity and tractability. Evidence suggests that the compromise chosen by description logics is a particularly successful one. However, description logic (as for all variants of firstorder logic) is severely limited in i ..."
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Cited by 119 (4 self)
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for its roles, and the properties of these fillers. We provide a semantics for PCLASSIC and an effective inference procedure for probabilistic subsumption: computing the probability that a random individual in class C is also in class D. The effectiveness of the algorithm relies
Stochastic simulation of chemical kinetics
 Annu. Rev. Phys. Chem
"... Abstract Stochastic chemical kinetics describes the time evolution of a wellstirred chemically reacting system in a way that takes into account the fact that molecules come in whole numbers and exhibit some degree of randomness in their dynamical behavior. Researchers are increasingly using this ap ..."
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Cited by 200 (0 self)
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this approach to chemical kinetics in the analysis of cellular systems in biology, where the small molecular populations of only a few reactant species can lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. After reviewing the supporting theory
Classical Logic and Computation
, 2000
"... This thesis contains a study of the proof theory of classical logic and addresses the problem of giving a computational interpretation to classical proofs. This interpretation aims to capture features of computation that go beyond what can be expressed in intuitionisticlogic. We introduce several ..."
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Cited by 73 (7 self)
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under cutelimination. Because our cutelimination procedures impose fewer constraints than previous procedures, we are ableto show how a fragment of classical logic can be seen as a typing system for the simplytyped lambda calculus extended with an erratic choice operator. As a pleasing consequence, we
Results 11  20
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6,062