Discrete Gaussian white noise
= Discrete Gaussian white noise
{title2=$\varepsilon_t\overset{\rm iid}{\sim}N(0,\sigma^2)$}
Discrete <Gaussian> <white noise> is a jointly <Gaussian> sequence with <expected value> zero and <covariance> $\sigma^2$ at lag zero and zero at other lags. Joint normality makes the components <independent>. This is a sequence of ordinary <random variables>, unlike the generalized continuous-time white-noise process.