Forecasting binary time series

I have a binary time series with 1 when the car is not moving, and 0 when the car is moving. I want to make a forecast for a time horizon up to 36 hours ahead and for each hour.

My first approach was to use a Naive Bayes using the following inputs: t-24 (daily seasonal), t-48 (weekly seasonal), hour of the day. However, the results are not very good.

Which articles or software do you recommend for this problem?


You can use generalized ARMA (GLARMA) models. See, for example, Kedem and Fokianos (2002), Regression Models for Time Series Analysis.

See also R package glarma (on CRAN)

Source : Link , Question Author : Ricardo Bessa , Answer Author : kjetil b halvorsen

Leave a Comment