- 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...
- econometrics,
autoregressive integrated moving average (ARIMA) and
seasonal ARIMA (SARIMA)
models are
generalizations of the
autoregressive moving average...
- 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 are a way to
describe 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...
-
given the
prompt (in bold) Like GPT-3, the
Llama series of
models are
autoregressive decoder-only Transformers, but
there are some
minor differences: SwiGLU...
- al.
Gaussian processes are a po****r
machine learning model. If an
auto-
regressive relationship between the data is ****umed, and each data
source is ****umed...
- general,
there are 3
classes of
language modelling tasks: "masked", "
autoregressive", and "prefixLM".
These classes are
independent of a
specific modeling...
- 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...
- autocorrelation, such as Unit root processes, trend-stationary processes,
autoregressive processes, and
moving average processes. In statistics, the autocorrelation...
