Results 251 to 260 of about 5,568,459 (279)
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2010
Broadening the scope of association models beyond the typical sociological and psychological fields, author Raymond Siu-Kwok Wong shows readers how to analyze and comprehend any social science data presented in cross-classified formats. Through a carful exposition of various association models, the text examines the underlying structure of odds-ratios,
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Broadening the scope of association models beyond the typical sociological and psychological fields, author Raymond Siu-Kwok Wong shows readers how to analyze and comprehend any social science data presented in cross-classified formats. Through a carful exposition of various association models, the text examines the underlying structure of odds-ratios,
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Technical-Associative Modelling
1991Since the CAD*I project started in 1984 a number of systems have become available which realize some aspects of the modelling concepts, described in Chapter 3. An overview of systems which, to some extent, include associative modelling techniques is given in Figure 5.1-1.
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Geometric-Associative Modelling
1991The goal of an advanced CAD-system is to provide a tool box of automated problem solving aids that allows a designer to conceive, evolve and document his design ideas. Above, it has been described a multi-level advanced modelling system. Because of the important role of geometric information in design, a requirement for an intelligent CAD-system is to ...
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2003
The two previous chapters involved modeling a random phenomenon X for which only one observed value was available.1 The information this value provided was not enough for us to deduce the random behavior of X,and this is why a prior information had to be introduced.
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The two previous chapters involved modeling a random phenomenon X for which only one observed value was available.1 The information this value provided was not enough for us to deduce the random behavior of X,and this is why a prior information had to be introduced.
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RStan Associative Learning Models
2020Associative learning models fit using Rstan for the manuscript Gorka et al. "Periaqueductal gray matter responses reflect negative prediction errors during the omission of aversive outcomes"
Gorka, Adam, Moraczewski, Dustin
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Association pattern language modeling
IEEE Transactions on Audio, Speech and Language Processing, 2006Statistical n-gram language modeling is popular for speech recognition and many other applications. The conventional n-gram suffers from the insufficiency of modeling long-distance language dependencies. This paper presents a novel approach focusing on mining long distance word associations and incorporating these features into language models based on
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Modeling radiative association kinetics
International Journal of Mass Spectrometry and Ion Processes, 1997Abstract New generic modeling results are shown for the radiative association of ions with neutrals. The approach used was based on the standard-hydrocarbon model of typical properties of ions and neutrals. A canonical phase space theory method was applied to calculate the kinetics with more confidence than previous RRKM-based results, and a ...
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Exploring and Modelling Association
2016In this chapter, we analyse the ideas of association, correlation and regression. We also discuss the underlying concepts that serve to model statistical relationships between variables and extend functional dependence to random situations. After describing how these ideas are introduced in high-school curricula, we present two teaching situations. The
Carmen Batanero, Manfred Borovcnik
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Modelling association football scores
Statistica Neerlandica, 1982Abstract  Previous authors have rejected the Poisson model for association football scores in favour of the Negative Binomial. This paper, however, investigates the Poisson model further. Parameters representing the teams' inherent attacking and defensive strengths are incorporated and the most appropriate model is found from a hierarchy of models ...
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International Journal of Materials Research, 2000
Krull, H., Singh, R., Sommer, F.
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Krull, H., Singh, R., Sommer, F.
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