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Declarative programming with rules

For the reasons described, no specific test will be advanced here as being superior, but Huber s model and the classical one for z = 2 and z = 3 are incorporated into program HUBER the authors are of the opinion that the best recourse is to openly declare all values and do the analysis twice, once with the presumed outliers included, and once excluded from the statistical analysis in the latter case the excluded points should nonetheless be included in tables (in parentheses) and in graphs (different symbol). Outliers should not be labeled as such solely on the basis of a fixed (statistical) rule the decision should primarily reflect scientific experience. The justification must be explicitly stated in any report cf. Sections 4.18 and 4.19. If the circumstances demand that a mle be set down, it is best to use a robust model such as Huber s its sensitivity for the problem at hand, and the typical rate for false positives, should be investigated by, for example, a Monte... [Pg.59]

ACT-R is composed of perceptual-motor and memory modules implemented as production rules. Both declarative and procedural memory are modeled. A pattern-matching mechanism is used to select production rules applicable to the situation. Buffers are used to interact with and represent the state of modules. ACT-R is implemented as a computer language. Users create a program containing relevant task data to model the task and task performance. An extension of ACT called SNIF-ACT that incorporates a Bayesian navigation mechanism was described earlier in this chapter (Fu and Pirolli 2007). [Pg.543]


See other pages where Declarative programming with rules is mentioned: [Pg.18]    [Pg.41]    [Pg.535]    [Pg.535]    [Pg.94]    [Pg.535]    [Pg.203]    [Pg.91]    [Pg.194]    [Pg.216]    [Pg.210]    [Pg.41]    [Pg.205]    [Pg.109]    [Pg.150]    [Pg.150]    [Pg.46]   
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