The Galton-Watson branching process is a second worked instance of a Markov chain — population size is itself a Markov chain on — chosen because it introduces a genuinely new tool, the probability generating function, needed precisely because the state space is infinite and the matrix methods of Discrete-Time Markov Chains do not directly apply. The topic is deliberately short: two lessons are enough to state Galton's 1873 extinction question, answer it completely via a generating-function fixed-point argument, and classify the three qualitatively different regimes the answer produces.
By the end of this topic you should be able to:
- set up a Galton-Watson process and compute its generating function's composition rule;
- state and apply the extinction probability theorem, including the geometric-offspring closed form;
- classify a process as subcritical, critical, or supercritical from its offspring mean, and describe the qualitatively different behaviour of each regime.
In this lesson
- Contents
- The big picture
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