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?

**Answer**

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)

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