I'm trying to simulate a person moving through a household using a Markov chain. Each state would be a room in the house. The issue I'm running into is that I have no existing data telling me what a typical person's activity pattern is (goal is to generate completely synthetic data), and so I have no starting point to compute state transition probabilities. How do I handle this? Is it sound to randomly assign these probabilities?
I found a paper (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.212.2548&rep=rep1&type=pdf) that I believe describes something similar. But I don't understand where they get the values in the diagrams they present in part 4.
Working with R.