• Facets (new session)
• Description
• Metadata
• Settings
  • Rule: ActivityStreamsMapasEquivalentb3sb3sifpdbprdf-labelfacetshttp://dbpedia.org/resource/inference/rules/dbpedia#http://dbpedia.org/resource/inference/rules/opencyc#http://dbpedia.org/resource/inference/rules/umbel#http://dbpedia.org/resource/inference/rules/yago#http://dbpedia.org/schema/property_rules#http://www.ontologyportal.org/inference/rules/SUMO#http://www.ontologyportal.org/inference/rules/WordNet#http://www.w3.org/2002/07/owl#ldpoplwebskos-transurn:det:rdf:labelvirtrdf-labelvirtrdf-urlNone
    
  • Inverse Functional Properties: Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects
  • "Same As": Disabled (fastest) Apply to subjects only Apply to objects only Apply to both subjects and objects (recommended) Apply to subjects, objects and predicates (not recommended on big datasets) Apply to predicates only (special use cases only)

About: Fractional model     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : owl:Thing, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)

In applied statistics, fractional models are, to some extent, related to binary response models. However, instead of estimating the probability of being in one bin of a dichotomous variable, the fractional model typically deals with variables that take on all possible values in the unit interval. One can easily generalize this model to take on values on any other interval by appropriate transformations. Examples range from participation rates in 401(k) plans to television ratings of NBA games.