Statistical model: Difference between revisions

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The '''stimulus–response model''' is a characterization of a [[statistical unit]] (such as a [[neuron]]) as a [[black box]] model, predicting a quantitative response to a quantitative [[stimulation|stimulus]], for example one administered by a researcher.
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==Fields of application==
 
Stimulus–response models are applied in international relations,<ref>
{{cite book
| title = What causes war?: an introduction to theories of international conflict
| chapter = International Interaction: Stimulus–Response Theory and Arms Races
| author = Greg Cashman
  | publisher = Lexington Books
| year = 2000
| isbn = 978-0-7391-0112-4
| pages = 160–192
| url = http://books.google.com/books?id=I9xIfeijGhMC&pg=PA167&dq=stimulus-response-model+statistical#v=onepage&q=stimulus-response-model%20statistical&f=false
}}</ref>
[[:en:Neuropsychological_test|psychology]],<ref>
{{cite book
| title = The Counselor's Companion: What Every Beginning Counselor Needs to Know
  | editor = Jocelyn Gregoire and Christin Jungers
| chapter = Counseling Across the Life Span
| author = Stephen P. Kachmar and Kimberly Blair
| publisher = Routledge
| year = 2007
| isbn = 978-0-8058-5684-2
| page = 143
| url = http://books.google.com/books?id=5V9nvsKeBgIC&pg=RA1-PA143&dq=stimulus-response-model++behavior#v=onepage&q=stimulus-response-model%20%20behavior&f=false
}}</ref>  
risk assessment,<ref>
{{cite book
| title = Analyzing environmental data
| chapter = Quantitative Risk Assessment with Stimulus–Response Data
| author = Walter W. Piegorsch and A. John Bailer
| publisher = John Wiley and Sons
| year = 2005
| isbn = 978-0-470-84836-4
| pages = 171–214
| url = http://books.google.com/books?id=FrNv8AwkoKgC&pg=PA172&dq=stimulus-response-model+statistical#v=onepage&q=stimulus-response-model%20statistical&f=false
}}</ref>
[[:en:Neuroscience|neuroscience]],<ref>
{{cite book
| title = Computer simulation in brain science
| chapter = Neurons with hysteresis?
| author = Geoffrey W. Hoffmann
| editor = Rodney Cotterill
| publisher = Cambridge University Press
| year = 1988
| isbn = 978-0-521-34179-0
| pages = 74–87
| url = http://books.google.com/books?id=B6nfz--ePEEC&pg=PA79&dq=stimulus-response++neuron#v=onepage&q=stimulus-response%20%20neuron&f=false
}}</ref>
neurally-inspired system design,<ref>
{{cite book
| title = Systems methodology for software
| author = Teodor Rus
| publisher = World Scientific
| year = 1993
| isbn = 978-981-02-1254-4
| page = 12
| url = http://books.google.com/books?id=l7o31p-6dlAC&pg=PA12&dq=stimulus-response-model++neuron#v=onepage&q=stimulus-response-model%20%20neuron&f=false
}}</ref>
and many other fields.
 
==Mathematical formulation==
 
The object of a stimulus–response model is to establish a mathematical function that describes the relation ''f'' between the stimulus ''x'' and the [[expected value]] (or other measure of location) of the response ''Y'':{{Citation needed|date=August 2009}}
 
: <math>E(Y) = f(x)</math>
 
A common simplification assumed for such functions is linear, thus we expect to see a relationship like
 
: <math>E(Y) = \alpha + \beta x.</math>
 
[[Statistical theory]] for [[linear model]]s has been well developed for more than fifty years, and a standard form of analysis called [[linear regression]] has been developed.
 
==References==
 
<references/>
 
{{DEFAULTSORT:Stimulus-Response Model}}
[[Category:Behavioral concepts]]
[[Category:Specific models]]
 
 
{{statistics-stub}}

Revision as of 08:21, 11 February 2014

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