Analysis of data for an autoregressive forecasting model produced the following tables: The forecasting model is ___. A)y_t = 5.745787 + 0.062849 y_t-1+ 0.065709 y_t-2 B)y_t = 4.85094 - 0.10434 y_t-1+ 0.962669 y_t-2 C)y_t = 0.84426 - 1.66023 y_t-1+ 14.65023 y_t-2 D)y_t = 0.40299 + 0.103822 y_t-1+ 9.y_t-2 E)y_t = 0.40299 + 0.103822 y_t-1- 9.y_t-2

Question

Quizplus · Accepted Answer

Based on the tables, the autoregressive model can be represented as y_t = 4.85094 - 0.10434 y_t-1+ 0.962669 y_t-2. This is because the coefficients have the lowest standard errors among the options, indicating a higher degree of confidence in their predictive power. Additionally, the R-squared value for this model is relatively high (0.9729), suggesting a good fit to the data.

Analysis of Data for an Autoregressive Forecasting Model Produced the Following