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31
View through a window may influence recovery from surgery
 Science
, 1984
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Risk reduction in large portfolios: Why imposing the wrong constraints helps
, 2002
"... Green and Hollifield (1992) argue that the presence of a dominant factor is why we observe extreme negative weights in meanvarianceefficient portfolios constructed using sample moments. In that case imposing noshortsale constraints should hurt whereas empirical evidence is often to the contrary. ..."
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Cited by 173 (5 self)
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Green and Hollifield (1992) argue that the presence of a dominant factor is why we observe extreme negative weights in meanvarianceefficient portfolios constructed using sample moments. In that case imposing noshortsale constraints should hurt whereas empirical evidence is often to the contrary. We reconcile this apparent contradiction. We explain why constraining portfolio weights to be nonnegative can reduce the risk in estimated optimal portfolios even when the constraints are wrong. Surprisingly, with noshortsale constraints in place, the sample covariance matrix performs as well as covariance matrix estimates based on factor models, shrinkage estimators, and daily data.
Multivariate tests of the zerobeta CAPM
 Journal of Financial Economics
, 1985
"... A ‘crosssectional regression test ’ (CSRT) of the CAPM is developed and its connection to the Hotelling T * test of multivariate statistical analysis is explored. Algebraic relations between the CSRT, the likelihood ratio test and the Lagrange multiplier test are derived and a useful smallsample b ..."
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Cited by 74 (7 self)
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A ‘crosssectional regression test ’ (CSRT) of the CAPM is developed and its connection to the Hotelling T * test of multivariate statistical analysis is explored. Algebraic relations between the CSRT, the likelihood ratio test and the Lagrange multiplier test are derived and a useful smallsample bound on the distribution function of the CSRT is obtained. An application of the CSRT suggests that the CRSP equallyweighted index is inefficient, but that the inefficiency is not explained by a firm sizeeffect from February to December. 1.
Term premiums in bond returns
 Journal of Political Economy
, 1975
"... portfolios. Expected bill returns are estimated from forward rates and from sample average returns. Both estimation methods indicate that expected returns on bills tend to peak at eight or nine months and never increase monotonically out to twelve months. Reliable inferences are limited to Treasury ..."
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Cited by 44 (1 self)
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portfolios. Expected bill returns are estimated from forward rates and from sample average returns. Both estimation methods indicate that expected returns on bills tend to peak at eight or nine months and never increase monotonically out to twelve months. Reliable inferences are limited to Treasury bills and thus to maturities up to a year. The variability of longerterm bond returns preempts precise conclusions about their expected returns. 1.
A paradigm for class prediction using gene expression profiles
 J. Comput. Biol
, 2002
"... We propose a general framework for prediction of predefined tumor classes using gene expression profiles from microarray experiments. The framework consists of 1) evaluating the appropriateness of class prediction for the given data set, 2) selecting the prediction method, 3) performing crossvalid ..."
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Cited by 33 (8 self)
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We propose a general framework for prediction of predefined tumor classes using gene expression profiles from microarray experiments. The framework consists of 1) evaluating the appropriateness of class prediction for the given data set, 2) selecting the prediction method, 3) performing crossvalidated class prediction and 4) assessing the significance of prediction results by permutation testing. We describe an application of the prediction paradigm to gene expression profiles from human breast cancers, with specimens classified as positive or negative for BRCA1 mutations and also for BRCA2 mutations. In both cases, the accuracy of class prediction was statistically significant when compared to the accuracy of prediction expected by chance. The framework proposed here for the application of class prediction is designed to reduce the occurrence of spurious findings, a legitimate concern for highdimensional microarray data. The prediction paradigm will serve as a good framework for comparing different prediction methods and may accelerate the development of molecular classifiers that are clinically useful. 2 Microarray technology has made possible the detailed molecular characterization of tumor specimens through the simultaneous measurement of mRNA expression levels for thousands of genes. These gene expression “profiles ” (as they are frequently called) can be used to discover biologically similar groups of tumors not previously recognized, to identify genes differentially expressed between two or more predefined groups, or to construct multivariate predictors of group membership. This paper addresses statistical considerations for the last of these goals, tumor class prediction. Examples include predicting whether or not a tumor will respond to a particular chemotherapy, predicting if a patient will be a longterm or shortterm survivor, and predicting which tumors possess a particular gene mutation.
Optimal Structure from Motion: Local Ambiguities and Global Estimates
, 2000
"... “Structure From Motion” (SFM) refers to the problem of estimating spatial properties of a threedimensional scene from the motion of its projection onto a twodimensional surface, such as the retina. We present an analysis of SFM which results in algorithms that are provably convergent and provably o ..."
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Cited by 30 (5 self)
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“Structure From Motion” (SFM) refers to the problem of estimating spatial properties of a threedimensional scene from the motion of its projection onto a twodimensional surface, such as the retina. We present an analysis of SFM which results in algorithms that are provably convergent and provably optimal with respect to a chosen norm. In particular, we cast SFM as the minimization of a highdimensional quadratic cost function, and show how it is possible to reduce it to the minimization of a twodimensional function whose stationary points are in onetoone correspondence with those of the original cost function. As a consequence, we can plot the reduced cost function and characterize the configurations of structure and motion that result in local minima. As an example, we discuss two local minima that are associated with wellknown visual illusions. Knowledge of the topology of the residual in the presence of such local minima allows us to formulate minimization algorithms that, in addition to provably converge to stationary points of the original cost function, can switch between different local extrema in order to converge to the global minimum, under suitable conditions. We also offer an experimental study of the distribution of the estimation error in the presence of noise in the measurements, and characterize the sensitivity of the algorithm using the structure of Fisher’s Information matrix.
Generalized twoparameter asset pricing models: Some empirical evidence
 Journal of Financial Economics
, 1978
"... A series of empirically refutable generalized two parameter asset pricing models that linearly relate risk and return are identified for the power (and quadratic) utility members of the linear risk tolerance capital asset pricing models. Five possible power utility models and the lhean variance mode ..."
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Cited by 2 (1 self)
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A series of empirically refutable generalized two parameter asset pricing models that linearly relate risk and return are identified for the power (and quadratic) utility members of the linear risk tolerance capital asset pricing models. Five possible power utility models and the lhean variance model are tested to determine whether one model might provide a more accurate description of security pricing. The major empirical result is that the data do not allow us to distinguish between the models. 1.
Animation Based in Dynamic Simulation Involving Irregular Objects with NonHomogeneous Roughness
 IEEE Computer Society: Proceedings on Computer Animation 2001, the Fourteenth Conference, Seoul, Korea
"... We propose a new technique that provides a unified framework for modeling the collision dynamics of objects having arbitrary shape and roughness. The technique assumes that boundary of the object is expressed by elementary segments with some random distribution of perturbation. Collision detection a ..."
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Cited by 2 (2 self)
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We propose a new technique that provides a unified framework for modeling the collision dynamics of objects having arbitrary shape and roughness. The technique assumes that boundary of the object is expressed by elementary segments with some random distribution of perturbation. Collision detection and treatment is done considering this conceptual representation. In order to efficiently detect collision between irregular objects, we introduce the aumented oriented bounded box tree. 1.
Oriented Bounding Boxes Based on Multiresolution Contours
 JOURNAL OF WSCG 2004
, 2004
"... The determination of intersection or contact points between objects in interference is not a simple task. It could be timeconsuming in a computer application. Generally, some real time applications use sophisticated algorithms based on hierarchical structure to isolate the segments of contours of o ..."
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Cited by 1 (0 self)
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The determination of intersection or contact points between objects in interference is not a simple task. It could be timeconsuming in a computer application. Generally, some real time applications use sophisticated algorithms based on hierarchical structure to isolate the segments of contours of objects in interference, to finally compute locally the contact points. Therefore, we are interested in search for the best way of constructing hierarchical structures bounding objects that allows us to quickly isolate the contour of segments in interference. To achieve that, the bounding must be adapted and fitted to the segments of the objects contours. In this work, we formulate a method to represent, in hierarchic structure, oriented rectangle boxes involving segments of object contours defined by closed cubical Bsplines curves. Each oriented box is computed in adapted and fitted form to the segments of the contour by using the second order statistical indicator on some elements of the segments of object contour in multiresolution representation.