Classification of the extinction probability by the mean #
Let q = bienaymeLaw μ {T | FiniteVertices T} be the probability that the tree is finite, for an
offspring probability measure μ with mean ∫⁻ k, k ∂μ in [0, ∞] (infinite mean allowed).
q ≤ sas soon asoffspringGF μ s ≤ s(a sub-fixed point bounds the iterates from above);- if the mean exceeds one, there is
s < 1withoffspringGF μ s ≤ s(exists_lt_one_offspringGF_le), henceq < 1(bienaymeLaw_finiteVertices_lt_one); q = 1exactly when the mean is at most one andμ {1} ≠ 1(bienaymeLaw_finiteVertices_eq_one_iff): forμ {1} = 1the tree is an infinite line andq = 0.
No source in PoissonDeclumping states the supercritical case, which the paper does not need.
Convexity and derivatives are not used: the bound 1 - f x ≥ x ^ N (1 - x) M comes from the
elementary inequality k x ^ N (1 - x) ≤ 1 - x ^ k for k ≤ N.
A sub-fixed point of the generating function bounds the probability of finiteness from above.
Supercritical case. For every offspring probability measure of mean greater than one,
possibly infinite, the tree is infinite with positive probability: q < 1.
For μ {1} = 1 the tree is an infinite line: the probability of finiteness is zero.
Classification. The probability that the tree is finite is 1 exactly when the mean is at
most one and μ {1} ≠ 1; otherwise it is < 1.