Handling irregular cut-offs

We'll be using a new dataset for this example. The World Food Programme (WFP) is the branch of the United Nations focused on hunger and food security. One of the greatest contributing factors to food security issues in developing countries that the WFP tracks is rainfall amounts because it can affect agricultural production. Thus, predicting rainfall is of critical importance in planning aid delivery.

This data represents the rainfall received over 30 years in one of the regions the WFP monitors. What makes this dataset unique is that the WFP recorded the amount of rain that accumulated at three times per month, on the 1st, the 11th, and the 21st. The accumulation from the 1st to the 11th is a 10-day period. It's the same with the 11th to the 21st. But the period from the 21st of one month to the 1st of the next varies depending upon the month. In a normal February, it will be 8 days. In a leap year, 9 days. Months of 30 and 31 days will see...