Time series analysis on small dataset


I am new to time series and therefore trying to feel my way around. I am required to do some analysis and possibly come up with a model. However, I have at most 2 years worth of quarterly data (at most 8 datapoints). Can I build any meaningful model based on the data? What possible model apart from linear regression with time as regressor can be built?



Posted 2018-08-01T21:49:59.853

Reputation: 1 047

1Not really. Eight data points wouldn’t even be enough for simple ordinary least squares regression, or even a t-test. I’d like to ask, what is it that you are trying to accomplish? What is your research question? – Jon – 2018-08-02T05:20:23.160

A graph would be useful (no need of the units). If you follow Tuker's advice, data visualization should become an automatic reflex. – AlainD – 2018-08-02T11:05:57.177



There is no valid answer. If you have a stationary process with 0 variance, then the forecast horizon has no limit.

More realistically, you have the follow rule of thumb (which is totally from experience with absolutely no theoretical base): the horizon forecast may be half the historical base. You have 8 data points, so you can forecast 4 points. You have 2 years, so you can forecast 1 year.

The key point is : check this after your forecast is done.


Posted 2018-08-01T21:49:59.853

Reputation: 256

Is there any mathematical proof for ´the horizon forecast may be half the historical base´or it is just based on experience? – Carlos Mougan – 2020-01-04T16:19:57.047

1A. Debcker, T. Modis, Determination of the uncertainties in S-curve logistic fits, Technological Forecasting and Social Change Volume 46, Issue 2, June 1994, Pages 153-173 – AlainD – 2020-04-04T08:11:34.157


As far as the time evolution model is concerned, you have:

  • A linear growth/decline. You increase/decrease of a constant value (in units, dollars,...)

  • A exponential growth/decline. You increase/decrease of a constant rate (in %)

  • A logistic growth/decline. You are filling a limited niche, and the increase in % is proportional to what remain to be filled.

  • Higher level of model (Bass-diffusion models,...), approximations (polynomials,...) or adaptive methods (moving average, exponential smoothing, ARIMA,...)

You can easily test exponential growth by fitting the log of your data on a linear regression, but other models require more sophisticated techniques.


Posted 2018-08-01T21:49:59.853

Reputation: 256

2Why do you not combine your two answers into one, e.g. using two heading, if you are making two different points? – n1k31t4 – 2018-08-02T11:03:09.233


I would start playing around with the prophet library for python, you can still make predictions with 8 datapoints, the accuracy is going to depend on a lot of things especially the variance in the points.


Posted 2018-08-01T21:49:59.853

Reputation: 1

2Suggesting someone try a statistical package does not address the issue of data quality/quantity which is OPs concern. – Jon – 2018-08-02T05:21:36.097