Random tree growth with general weight function

We extend the results of B. Bollobas, O. Riordan, J. Spencer, G. Tusnady, and Mori. We consider a model of random tree growth, where at each time unit a new node is added and attached to an already existing node chosen at random. The probability with which a node with degree $k$ is chosen is proportional to $w(k)$, where $w$ is a fixed weight function. We prove that if $w$ fulfills some asymptotic requirements then the degree sequence converges in probability, we give the limit. In particular if $w$ is asymptotically linear then the degree sequence decays with power law. Our method of proof is analytic rather than combinatorial, having the advantage of robustness: only asymptotic properties of the weight function $w$ are used, while in the cited papers the explicit law $w(k)=ak+b$ is assumed.