# How to forecast with time series of different length?

I am new to time series analysis, and I am wondering how I can approach forecasting having time series of different lengths. Specifically, each time series contains a sequence of ages and value. E.g.,

age_t value_t age_t-1 value_t-1


such as

12 210 11 205 10 203 9 203 ... 2 340 1 350
3 340 2 335 1 392


I want to forecast value_t+1. My problem is that I have time series of different lengths: for certain machines I have 15 years of history, for other machines I have 1-2 years of history.

Could anyone suggest a general way of approaching forecasting in this case, e.g., how to pre-process/transform the time series, or a method that is typically indicated in cases like this?

• You could assume a sequence length. If the length of the time series is greater than that of the sequence length, cut it. If it's smaller than that left pad it with (0, 0). – Fariborz Ghavamian Aug 30 at 13:57