Time Series
Observations indexed by time, where the sequence itself is data. Trend, seasonality, cycles and noise — and the distinction most summaries get wrong.
Observations indexed by time, where the sequence itself is data. Trend, seasonality, cycles and noise — and the distinction most summaries get wrong.
The rolling alarm fires on three days and stays quiet on seventy-four while the latency stays 40 ms high the whole time.
Prophet offers configurable forecasting at scale. Two FPP3 examples favor other methods on accuracy; assess its performance on your own series and forecast horizon.
The value from the same season one period ago. Where it appears in the ACF, what seasonal differencing does with it, and why it is expensive in data.
A repeating pattern tied to the calendar. What separates it from a cycle, and why confusing the two produces forecasts the data never supported.