100 Facts About Prediction and Forecasting

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Here are 100 facts about prediction and forecasting:

1. Prediction vs. Forecasting: Prediction is a general term for estimating future outcomes, while forecasting specifically refers to predicting future values based on historical data.
2. Deterministic Models: Make predictions based solely on input variables, without considering randomness.
3. Stochastic Models: Incorporate randomness into predictions, recognizing the inherent uncertainty in future outcomes.
4. Autoregressive Integrated Moving Average (ARIMA): A popular time series forecasting method combining autoregression, differencing, and moving averages.
5. Exponential Smoothing Methods: Include Simple Exponential Smoothing, Double Exponential Smoothing (Holt’s method), and Triple Exponential Smoothing (Holt-Winters method).
6. Long Short-Term Memory (LSTM): A type of recurrent neural network (RNN) used for sequence prediction and forecasting.
7. Seasonal Decomposition of Time Series (STL): Decomposes time series data into seasonal, trend, and residual components for better forecasting.
8. Naive Forecasting: Assumes future values will be the same as the most recent historical value.
9. White Noise: A series of random data points with no…