AR Model: Find the Parameters

$0/2$ puntos $($calificados$)$

Using the lag $p$ from the previous problem, fit an $AR(p)$ model to the residual in the training period. Recall the

AR $(p)$ model:

$x_t={}_1{x}_{t-1}+$dots$+{}_p{x}_{t-p}+{}_t$

Report the coefficients ${}_1$ and ${}_2($up to $2$ significant digits$).$

Python tip: You may use AutoReg from statsmodels. See documentation on AutoReg. The model used by

AutoReg can include linear trends as controlled by the parameter trend. It also allows a contant term:

$x_t=c+{}_1{x}_{t-1}+$dots$+{}_p{x}_{t-p}+{}_t.$ The grader is tolerant of different reasonable answers.

${}_1=$

${}_2=$

Plot the final model predictions and the actual observed data together to visualize the fit. $($This final task is not

graded$).$