Missing time-series vs. Empty time-series

Lokad is about time-series forecasting, but as simple as the time-series model may seem to be (after all a time-series is nothing more than a list of time-value pairs), there are several subtleties in the way to manage time-series. In this post, we will see how the Lokad time-series model distinguishes missing time-value pairs from empty time-value pairs. Since the topic is slightly complex, I would suggest, if you’re not familiar the Lokad technology, to have a look at our User Guide (in particular, the Forecasting tasks section).

A practical situation

Let’s start with a practical real-life situation; let’s assume that we have a time-series that include 12 time-values, one value for each month of the year 2005 (starting January 2005, ending December 2005). We can imagine that this time-series represent the monthly sales of a web shop. At the time I am writing this post, it’s the beginning of January 2007. What happen if I insert now this time-series into my Lokad account and ask for a monthly forecast? Well, there is an ambiguity in the time-series model, because there would be two possibilities:

Let’s make the things clear: Lokad has chosen the data-centric approach, if ask a monthly forecast for your 12 time-values ranging from January 2005 to December 2005, you will get a forecast for January 2006, no matter if you request the forecast at the beginning of 2006 or in a distant future. Lokad takes the last time-value pair of your time-series as a reference to compute the forecasts. This option has been chosen because we believe it’s closer to the business requirements.

Some arguments supporting the data-centric approach

Let’s review the arguments in favor of the data-centric approach:

Yet, this approach involves a minor drawback: you need to handle explicitly the lack of data. For example, in the previous web shop situation, each product of the catalog may not have be sold even once a month. In such case, you must explicitly add a zero time-value in your time-series that represent this lack of sales.