/time-series-exercises

Time Series: Analyzing, Modeling, Forecasting Temporal Events

Primary LanguageJupyter Notebook

Time_Series_README.md

James Allen

Time Series: Analyzing, Modeling, Forecasting Temporal Events

"Time is not a line, but a series of now-points." -Taisen Deshimaru

Time series vocabulary

  • Temporal: Relating to time.
  • Periodic: Occurring at intervals.
  • Resampling in Time Sereis: Changing the frequency of your data points.
  • Stationary Process: Distribution does not change over time.
  • Trend: Long term progression (increasing, decreasing, e.g.)
  • Seasonality: Changes in patterns due to seasonal factors.
  • Heteroskedasticity: Changes in variance over time.
  • Autocorrelation: 'Regression of self', used to detect non-randomness in data. It is a correlation coefficient, but instead of between two different variables, it is between the values of the same variable at two different times.
  • Lag Variables: Previous time steps.