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Advances in Prospect Theory: Cumulative Representation of Uncertainty
 JOURNAL OF RISK AND UNCERTAINTY, 5:297323 (1992)
, 1992
"... We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows differ ..."
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Cited by 1717 (17 self)
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We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows
Blind Beamforming for Non Gaussian Signals
 IEE ProceedingsF
, 1993
"... This paper considers an application of blind identification to beamforming. The key point is to use estimates of directional vectors rather than resorting to their hypothesized value. By using estimates of the directional vectors obtained via blind identification i.e. without knowing the arrray mani ..."
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Cited by 719 (31 self)
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This paper considers an application of blind identification to beamforming. The key point is to use estimates of directional vectors rather than resorting to their hypothesized value. By using estimates of the directional vectors obtained via blind identification i.e. without knowing the arrray
Shapley Mappings and the Cumulative Value for nPerson Games with Fuzzy Coalitions
"... In this paper we prove the existence and uniqueness of a solution concept for nperson games with fuzzy coalitions, which we call the Shapley mapping. The Shapley mapping, when it exists, associates to each fuzzy coalition in the game an allocation of the coalitional worth satisfying the efficiency, ..."
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Cited by 4 (0 self)
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, the symmetry, and the nullplayer conditions. It determines a “cumulative value ” that is the “sum ” of all coalitional allocations and for whose computation we provide an explicit formula.
Market Timing and Capital Structure
 THE JOURNAL OF FINANCE • VOL. LVII, NO. 1 • FEB. 2002
, 2002
"... It is well known that firms are more likely to issue equity when their market values are high, relative to book and past market values, and to repurchase equity when their market values are low. We document that the resulting effects on capital structure are very persistent. As a consequence, curren ..."
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Cited by 427 (13 self)
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, current capital structure is strongly related to historical market values. The results suggest the theory that capital structure is the cumulative outcome of past attempts to time the equity market.
The Network Structure of Social Capital
 RESEARCH IN ORGANIZATIONAL BEHAVIOR (VOL
, 2000
"... This is a review of argument and evidence on the connection between social networks and social capital. My summary points are three: (1) Research and theory will better cumulate across studies if we focus on the network mechanisms responsible for social capital effects rather than trying to integrat ..."
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Cited by 380 (1 self)
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This is a review of argument and evidence on the connection between social networks and social capital. My summary points are three: (1) Research and theory will better cumulate across studies if we focus on the network mechanisms responsible for social capital effects rather than trying
Strictly Proper Scoring Rules, Prediction, and Estimation
, 2007
"... Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if the forecaster maximizes the expected score for an observation drawn from the distribution F if he ..."
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Cited by 373 (28 self)
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Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if the forecaster maximizes the expected score for an observation drawn from the distribution F
Approximating probabilistic inference in Bayesian belief networks is NPhard
, 1991
"... Abstract A belief network comprises a graphical representation of dependencies between variables of a domain and a set of conditional probabilities associated with each dependency. Unless P=NP, an efficient, exact algorithm does not exist to compute probabilistic inference in belief networks. Stoch ..."
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Cited by 291 (4 self)
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. Stochastic simulation methods, which often improve run times, provide an alternative to exact inference algorithms. We present such a stochastic simulation algorithm 2)BNRAS that is a randomized approximation scheme. To analyze the run time, we parameterize belief networks by the dependence value PE, which
WaveletBased Histograms for Selectivity Estimation
"... Query optimization is an integral part of relational database management systems. One important task in query optimization is selectivity estimation, that is, given a query P, we need to estimate the fraction of records in the database that satisfy P. Many commercial database systems maintain histog ..."
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Cited by 245 (16 self)
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. Histograms built on the cumulative data values give very good approximations with limited space usage. We give fast algorithms for constructing histograms and using
Stochastic Trends and Economic Fluctuations
 American Economic Review
, 1991
"... Are business cycles mainly the result of permanent shocks to productivity? This paper uses a longrun restriction implied by a large class of realbusinesscycle modelsidentifying permanent productivity shocks as shocks to the common stochastic trend in output, consumption, and investmentto provid ..."
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Cited by 253 (9 self)
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typically explain less than half of the businesscycle variability in output, consumption, and investment. (JEL E32, C32) A central, surprising, and controversial result of some current research on real business cycles is the claim that a common stochastic trendthe cumulative effect of permanent shocks
Bayesian inference on phylogeny and its impact on evolutionary biology.
 Science
, 2001
"... 1 As a discipline, phylogenetics is becoming transformed by a flood of molecular data. These data allow broad questions to be asked about the history of life, but also present difficult statistical and computational problems. Bayesian inference of phylogeny brings a new perspective to a number of o ..."
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Cited by 235 (10 self)
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combinations of branch length and substitution model parameter values. It is all but impossible to do this analytically. Fortunately, a number of numerical methods are available that allow the posterior probability of a tree to be approximated, the most useful of which is Markov chain Monte Carlo [MCMC (4
Results 1  10
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2,745