- In statistics, econometrics, and
signal processing, an
autoregressive (AR)
model is a
representation of a type of
random process; as such, it can be used...
- In econometrics, the
autoregressive conditional heteroskedasticity (ARCH)
model is a
statistical model for time
series data that
describes the variance...
- econometrics,
autoregressive integrated moving average (ARIMA) and
seasonal ARIMA (SARIMA)
models are
generalizations of the
autoregressive moving average...
- In the
statistical analysis of time series,
autoregressive–moving-average (ARMA)
models are a way to
describe of a (weakly)
stationary stochastic process...
-
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...
-
Language Model Meta AI,
formerly stylized as LLaMA) is a
family of
autoregressive large language models (LLMs)
released by Meta AI
starting in February...
- 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...
- In time
series modeling, a
nonlinear autoregressive exogenous model (NARX) is a
nonlinear autoregressive model which has
exogenous inputs. This means...
- 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...
