January 2019
Intermediate to advanced
294 pages
6h 43m
English
Content preview from Machine Learning Quick Reference
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White noise
A simple series with a collection of uncorrelated random variables with a mean of zero and a standard deviation of σ2 is called white noise. In this, variables are independent and identically distributed. All values have the same variance of σ2. In this case, the series is drawn from Gaussian distribution, and is called Gaussian white noise.
When the series turns out to be white noise, it implies that the nature of the series is totally random and there is no association within the series. As a result, the model can't be developed, and prediction is not possible in this scenario.
However, when we typically build a time series model with a nonwhite noise series, we try to attain a white noise phenomenon within the residuals or ...
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