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The relationship between return and market value of common stocks
 Journal of Financial Economics
, 1981
"... This study examines the empirical relattonship between the return and the total market value of NYSE common stocks. It is found that smaller firms have had htgher risk adjusted returns, on average, than larger lirms. This ‘size effect ’ has been in existence for at least forty years and is evidence ..."
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Cited by 787 (0 self)
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This study examines the empirical relattonship between the return and the total market value of NYSE common stocks. It is found that smaller firms have had htgher risk adjusted returns, on average, than larger lirms. This ‘size effect ’ has been in existence for at least forty years and is evidence
Semantic similarity based on corpus statistics and lexical taxonomy
 Proc of 10th International Conference on Research in Computational Linguistics, ROCLING’97
, 1997
"... This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantifie ..."
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Cited by 870 (0 self)
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calculation. When tested on a common data set of word pair similarity ratings, the proposed approach outperforms other computational models. It gives the highest correlation value (r = 0.828) with a benchmark based on human similarity judgements, whereas an upper bound (r = 0.885) is observed when human
Spurious Regressions in Econometrics
 Journal of Econometrics
, 1974
"... It is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the DurbinWatson statistic. We f ..."
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Cited by 794 (6 self)
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It is very common to see reported in applied econometric literature time series regression equations with an apparently high degree of fit, as measured by the coefficient of multiple correlation R2 or the corrected coefficient R2, but with an extremely low value for the DurbinWatson statistic. We
Random forests
 Machine Learning
, 2001
"... Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the fo ..."
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Cited by 3601 (2 self)
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Abstract. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees
Motivational and selfregulated learning components of classroom academic performance
 Journal of Educational Psychology
, 1990
"... A correlational study examined relationships between motivational orientation, selfregulated learning, and classroom academic performance for 173 seventh graders from eight science and seven English classes. A selfreport measure of student selfefficacy, intrinsic value, test anxiety, selfregulat ..."
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Cited by 675 (6 self)
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A correlational study examined relationships between motivational orientation, selfregulated learning, and classroom academic performance for 173 seventh graders from eight science and seven English classes. A selfreport measure of student selfefficacy, intrinsic value, test anxiety, self
Image denoising using a scale mixture of Gaussians in the wavelet domain
 IEEE TRANS IMAGE PROCESSING
, 2003
"... We describe a method for removing noise from digital images, based on a statistical model of the coefficients of an overcomplete multiscale oriented basis. Neighborhoods of coefficients at adjacent positions and scales are modeled as the product of two independent random variables: a Gaussian vecto ..."
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Cited by 512 (17 self)
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vector and a hidden positive scalar multiplier. The latter modulates the local variance of the coefficients in the neighborhood, and is thus able to account for the empirically observed correlation between the coefficient amplitudes. Under this model, the Bayesian least squares estimate of each
The Varieties of Reference
, 1982
"... Tracing the development of concepts of affect and emotion in mathematics education (ME) research is informative for research on teaching statistics. In both areas, early research focused on more stable aspects of affect beliefs, values and attitudes using surveys to study dimensionality, and corre ..."
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Cited by 543 (2 self)
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Tracing the development of concepts of affect and emotion in mathematics education (ME) research is informative for research on teaching statistics. In both areas, early research focused on more stable aspects of affect beliefs, values and attitudes using surveys to study dimensionality
Sequential bargaining with correlated values
 Review of Economic Studies
, 1989
"... The paper analyzes an infinitehorizon sequential bargaining game (with onesided offers) between a buyer and a seller when the buyer's valuation depends on the seller's; the seller knows the value of the object and the buyer does not. The influence of relative discount factors on the solu ..."
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Cited by 32 (0 self)
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The paper analyzes an infinitehorizon sequential bargaining game (with onesided offers) between a buyer and a seller when the buyer's valuation depends on the seller's; the seller knows the value of the object and the buyer does not. The influence of relative discount factors
ModelBased Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application
, 2001
"... Background: A modelbased analysis of oligonucleotide expression arrays we developed previously uses a probesensitivity index to capture the response characteristic of a specific probe pair and calculates modelbased expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
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Cited by 774 (28 self)
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's presence in many arrays of an array set allows the probesensitivity index to be estimated accurately. We extended the model to obtain expression values for PMonly arrays, and found that the 20probe PMonly model is comparable to the 10probe PM/MM difference model, in terms of the expression
A Comparative Study on Feature Selection in Text Categorization
, 1997
"... This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI), ..."
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Cited by 1322 (15 self)
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precision) . DF thresholding performed similarly. Indeed we found strong correlations between the DF, IG and CHI values of a term. This suggests that DF thresholding, the simplest method with the lowest cost in computation, can be reliably used instead of IG or CHI when the computation of these measures
Results 1  10
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