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. The Model is well used in 'study of consumer response' to various stimulus as - Business Environment and marketing mix.
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Fields of application
Stimulus–response models are applied in international relations, psychology, risk assessment, neuroscience, neurally-inspired system design, 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:
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.