@article{fdi:010052991,
  title = {{A}nalytical models approximating individual processes : a validation method},
  author = {{F}avier, {C}. and {D}{\'e}gallier, {N}icolas and {M}enk{\`e}s, {C}hristophe},
  editor = {},
  language = {{ENG}},
  abstract = {{U}pscaling population models from fine to coarse resolutions, in space, time and/or level of description, allows the derivation of fast and tractable models based on a thorough knowledge of individual processes. {T}he validity of such approximations is generally tested only on a limited range of parameter sets. {A} more general validation test, over a range of parameters, is proposed; this would estimate the error induced by the approximation, using the original model's stochastic variability as a reference. {T}his method is illustrated by three examples taken from the field of epidemics transmitted by vectors that bite in a temporally cyclical pattern, that illustrate the use of the method: to estimate if an approximation over- or under-fits the original model; to invalidate an approximation; to rank possible approximations for their qualities. {A}s a result, the application of the validation method to this field emphasizes the need to account for the vectors' biology in epidemic prediction models and to validate these against finer scale models.},
  keywords = {{M}odel upscaling ; {I}ndividual-based models ; {P}opulation-level models ; {S}tatistical tests ; {E}pidemic models ; {C}yclically feeding vectors},
  booktitle = {},
  journal = {{M}athematical {B}iosciences},
  volume = {228},
  numero = {2},
  pages = {127--135},
  ISSN = {0025-5564},
  year = {2010},
  DOI = {10.1016/j.mbs.2010.08.014},
  URL = {https://www.documentation.ird.fr/hor/fdi:010052991},
}