- "infer" computes residuals based on how well the model fits the known data, while "forecast" predicts future values and compares them to actual data, reflecting predictive accuracy.
- Both functions use initial conditions differently; "infer" focuses on fitting within the known dataset, whereas "forecast" extends beyond the training data for predictions.
forecast vs. infer
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Hi,
Let's have a stationary data with 100 elements. Let's use the first 70 for defining an appropriate ARIMA model (EstMdl), and use the last 30 for tests. Test 1: infering residuals for the last 30 elements: E = infer(EstMdl,data(71:100),'Y0',dat(1:70)); Test 2: forecasting the last 30 elements: OUT = forecast(EstMdl,30,'Y0',dat(1:70)); then determining the residual as: res = data(71:100)-OUT;
According to my understanding, res should be equal to E. But they are not. Why?
Regards Lorant
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回答 (1 件)
Aman
2024 年 10 月 7 日
As per my understanding, you want to know why there is discrepancy in the output of the two functions.
The difference is coming due to the below two reasons:
I hope it clears your doubt :)
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