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Review of Regression Models for Categorical Dependent Variables Using Stata, Second
"... Abstract. This article reviews Regression Models for Categorical Dependent ..."
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Abstract. This article reviews Regression Models for Categorical Dependent
Interprocedural Slicing Using Dependence Graphs
 ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS
, 1990
"... ... This paper concerns the problem of interprocedural slicinggenerating a slice of an entire program, where the slice crosses the boundaries of procedure calls. To solve this problem, we introduce a new kind of graph to represent programs, called a system dependence graph, which extends previou ..."
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Cited by 837 (84 self)
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previous dependence representations to incorporate collections of procedures (with procedure calls) rather than just monolithic programs. Our main result is an algorithm for interprocedural slicing that uses the new representation. (It should be noted that our work concerns a somewhat restricted kind
PROBABILITY INEQUALITIES FOR SUMS OF BOUNDED RANDOM VARIABLES
, 1962
"... Upper bounds are derived for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt. It is assumed that the range of each summand of S is bounded or bounded above. The bounds for Pr(SES> nt) depend only on the endpoints of the ranges of the s ..."
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Cited by 2215 (2 self)
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of the smumands and the mean, or the mean and the variance of S. These results are then used to obtain analogous inequalities for certain sums of dependent random variables such as U statistics and the sum of a random sample without replacement from a finite population.
Financial Dependence and Growth
 American Economic Review
, 1998
"... This paper examines whether nancial development facilitates economic growth by scrutinizing one rationale for such a relationship; that nancial development reduces the costs of external nance to rms. Speci cally, we ask whether industrial sectors that are relatively more in need of external nance de ..."
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Cited by 1086 (26 self)
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develop disproportionately faster in countries with more developed nancial markets. We nd this to be true in a large sample of countries over the 1980s. We show this result is unlikely to be driven by omitted variables, outliers, or reverse causality. (JEL O4, F3, G1) A large literature, dating at least
Using Bayesian networks to analyze expression data
 Journal of Computational Biology
, 2000
"... DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a “snapshot ” of transcription levels within the cell. A major challenge in computational biology is to uncover, from such measurements, gene/protein interactions and key biologica ..."
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Cited by 1088 (17 self)
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biological features of cellular systems. In this paper, we propose a new framework for discovering interactions between genes based on multiple expression measurements. This framework builds on the use of Bayesian networks for representing statistical dependencies. A Bayesian network is a graphbased model
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 3613 (2 self)
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in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund & R
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
, 2002
"... We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language senten ..."
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Cited by 508 (30 self)
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We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language
A model for technical inefficiency effects in a stochastic frontier production function for panel data
 Empirical Economics
, 1995
"... Abstract: A stochastic frontier production function is defined for panel data on firms, in which the nonnegative technical inetGciency effects are assumed to be a function of firmspecific variables and time. The inefficiency effects are assumed to be independently distributed as truncations of nor ..."
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Cited by 555 (4 self)
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using up to ten years of data on paddy farmers from an Indian village. The null hypotheses, that the inefficiency effects are not stochastic or do not depend on the farmerspecific variables and time of observation, are rejected for these data.
A theory of timed automata
, 1999
"... Model checking is emerging as a practical tool for automated debugging of complex reactive systems such as embedded controllers and network protocols (see [23] for a survey). Traditional techniques for model checking do not admit an explicit modeling of time, and are thus, unsuitable for analysis of ..."
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Cited by 2651 (32 self)
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using finitely many realvalued clock variables. Automated analysis of timed automata relies on the construction of a finite quotient of the infinite space of clock valuations. Over the years, the formalism has been extensively studied leading to many results establishing connections to circuits
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