Searching over model order
In this exercise you are faced with a dataset which appears to be an ARMA model. You can see the ACF and PACF in the plot below. In order to choose the best order for this model you are going to have to do a search over lots of potential model orders to find the best set.
<\center>The ARIMA model class and the time series DataFrame df are available in your environment.
This exercise is part of the course
ARIMA Models in Python
Exercise instructions
- Loop over values of
pfrom 0-2. - Loop over values of
qfrom 0-2. - Train and fit an ARMA(p,q) model.
- Append a tuple of
(p,q, AIC value, BIC value)toorder_aic_bic.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create empty list to store search results
order_aic_bic=[]
# Loop over p values from 0-2
for p in range(____):
# Loop over q values from 0-2
for q in range(____):
# create and fit ARMA(p,q) model
model = ARIMA(df, order=____)
results = model.fit()
# Append order and results tuple
order_aic_bic.append((____))