A Conceptual Vocalubary of Time Series Analysis

 Search full text

Browse the glossary using this index

Special | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | ALL

Page: (Previous)   1  2
ALL

W

white noise

The time series generated from uncorrelated variables $$w_t$$ with mean 0 and finite variance $$\sigma^2_w$$ is called white noise and denoted as $$w_t \sim wn(0, \sigma^2_w).$$  The designation white originates from the analogy with white light and indicates that all possible periodic oscillations are present with equal strength.

If uncorrelated variables $$w_t$$s are further independent and identically distributed (iid) the process is a white independent noise and denoted as $$w_t \sim iid(0, \sigma^2_t).$$

If $$w_t$$ are independent normal random variables, with mean 0 and variance $$\sigma^2_w$$, the process $$w_t \sim N(0, \sigma^2_t)$$ is called Gaussian white noise.

Page: (Previous)   1  2
ALL