- In statistics, econometrics, and
signal processing, an
autoregressive (AR)
model is a
representation of a type of
random process; as such, it is used to...
- In econometrics, the
autoregressive conditional heteroskedasticity (ARCH)
model is a
statistical model for time
series data that
describes the variance...
- In the
statistical analysis of time series,
autoregressive–moving-average (ARMA)
models provide a
parsimonious description of a (weakly)
stationary stochastic...
- in time
series analysis, an
autoregressive integrated moving average (ARIMA)
model is a
generalization of an
autoregressive moving average (ARMA) model...
-
Threshold AutoRegressive. For some
background history, see Tong (2011, 2012). The
models can be
thought of in
terms of
extension of
autoregressive models...
-
statisticians George Box and
Gwilym Jenkins,
applies autoregressive moving average (ARMA) or
autoregressive integrated moving average (ARIMA)
models to find...
- cross-correlated with a non-identical to
itself random-variable.
Together with the
autoregressive (AR) model, the moving-average
model is a
special case and key component...
- role in data
analysis aimed at
identifying the
extent of the lag in an
autoregressive (AR) model. The use of this
function was
introduced as part of the Box–Jenkins...
- with autocovariance. Unit root processes, trend-stationary processes,
autoregressive processes, and
moving average processes are
specific forms of processes...
-
series modeling, a
nonlinear autoregressive exogenous model (NARX) is a nonlinear[disambiguation needed]
autoregressive model which has
exogenous inputs...
