In
statistics and
signal processing, an
autoregressive (
AR)
model is a representation of a type of
random process; as such, it describes certain time-varying processes in
nature,
economics, etc. The autoregressive model specifies that the output variable depends
linearly on its own previous values and on a
stochastic term (a
stochastic—an imperfectly predictable—term); thus the model is in the form of a
stochastic difference equation. It is a special case of the more general
ARMA model of
time series, which has a more complicated stochastic structure; it is also a special case of the
vector autoregressive model (VAR), which consists of a system of more than one stochastic difference equation.