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Time series are data observed over time (either in continuous time or at discrete time periods).
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How to forecast time-series bounded by [0,1], i.e., forecast relative frequencies?
Prof. Hyndman points out this approach in his comment above:
"...transform the data using a scaled logit transform which maps (a,b) to the whole real line:
$$y = \log\left(\frac{x-a}{b-x}\right)$ …
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How to forecast time-series bounded by [0,1], i.e., forecast relative frequencies?
I am working with time series values which are all in the closed interval [0, 1]; these values represent relative frequencies, i.e., empirical probabilities. I would like to create a model such that a …