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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 stimulus, for example one administered by a researcher.
Fields of application
Stimulus-response models are applied in international relations,psychology,risk assessment,neuroscience, neurally-inspired system design, and many other fields.
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:
A common simplification assumed for such functions is linear, thus we expect to see a relationship like
Statistical theory for linear models has been well developed for more than fifty years, and a standard form of analysis called linear regression has been developed.