An asymptotic maximum principle for essentially linear evolution models
| dc.creator | Baake, E. | |
| dc.creator | Baake, M. | |
| dc.creator | Bovier, A. | |
| dc.creator | Klein, M. | |
| dc.date | 2003-11-13 | |
| dc.date | 2004-06-08 | |
| dc.date.accessioned | 2026-07-07T06:28:56Z | |
| dc.date.available | 2026-07-07T06:28:56Z | |
| dc.description | Recent work on mutation-selection models has revealed that, under specific assumptions on the fitness function and the mutation rates, asymptotic estimates for the leading eigenvalue of the mutation-reproduction matrix may be obtained through a low-dimensional maximum principle in the limit N to infinity (where N is the number of types). In order to extend this variational principle to a larger class of models, we consider here a family of reversible N by N matrices and identify conditions under which the high-dimensional Rayleigh-Ritz variational problem may be reduced to a low-dimensional one that yields the leading eigenvalue up to an error term of order 1/N. For a large class of mutation-selection models, this implies estimates for the mean fitness, as well as a concentration result for the ancestral distribution of types. | |
| dc.description | 31 pages, 2 figures. Thorough revision, additional material included. J. Math. Biol., in press | |
| dc.identifier | https://arxiv.org/abs/q-bio/0311020 | |
| dc.identifier | http://arxiv.org/abs/q-bio/0311020 | |
| dc.identifier | J. Math. Biol. 50 (2005), 83--114 | |
| dc.identifier | doi:10.1007/s00285-004-0281-7 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/97866 | |
| dc.subject | Populations and Evolution | |
| dc.title | An asymptotic maximum principle for essentially linear evolution models | |
| dc.type | text |