What are the best practices for time series modeling?

What are the best practices for time series modeling?

Some best practices include ensuring data quality, selecting appropriate models, and validating results.

How do I handle missing values in my time series data?

You can handle missing values by interpolation, forward filling, or using models that accommodate missing data.

What models are commonly used for time series forecasting?

Common models include ARIMA, Exponential Smoothing, and machine learning approaches like LSTM.

How can I evaluate the performance of my time series model?

You can evaluate performance using metrics like Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and AIC.