Answer:
Explanation:
Out of the choices you provided, linearity is not a component of a time series.
Here's why:
Time series components are the underlying patterns or variations that exist within the data over time. These components help us understand the behavior of the data and make predictions about future values.
The common components of a time series include:
Trend: Long-term increase or decrease in the data.
Seasonality: Repeating patterns at fixed intervals (e.g., daily, weekly, yearly).
Cyclicity: Fluctuations that occur over a longer, irregular time period.
Irregularity: Random variations in the data that cannot be explained by other components.
Linearity refers to whether the relationship between the time variable and the data points is linear (straight line) or non-linear (curved line). While linearity can be a characteristic observed in a time series trend, it's not a fundamental component itself. A time series can exhibit linear or non-linear trends.
