A higher MSE indicates that the model’s predictions are less accurate.
A one-sided curve refers to a filter that only depends on past values (or past and present values), not future values, also known as causal filters.
A one-sided moving average uses only past values, while a two-sided moving average includes future values as well.
MSE = (1/n) * Σ(y_{i} - ŷ_{i})^2, where y_{i} is the actual value and ŷ_{i} is the predicted value.
For a one-sided moving average, the formula is y_{t} = (y_{t-2} + y_{t-1} + y_{t}) / 3.
A lower MSE indicates that the model’s predictions are closer to the actual data.
MSE measures the average squared difference between the observed actual values and the values predicted by a model.
One-sided curves are important because they allow predictions to be made using only current and past data, which is essential for real-time forecasting.
