2. You Should Know about Time Series Forecasting in R

Components of Time Series

To use time-series data and develop a model, you need to understand the patterns in the data over time. These patterns are classified into four components, which are:

  • Trend

It represents the gradual change in the time series data. The trend pattern depicts long-term growth or decline.

  • Level

It refers to the baseline values for the series data if it were a straight line.

  • Seasonality

It represents the short-term patterns that occur within a single unit of time and repeats indefinitely.

  • Noise

It represents irregular variations and is purely random. These fluctuations are unforeseen, unpredictable, and cannot be explained by the model.

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