@inproceedings{fdi:010067309,
  title = {{V}ariables selection by the {LASSO} method : application to malaria data of {T}ori-{B}ossito ({B}enin)},
  author = {{K}ouwaye, {B}.{T}. and {F}onton, {N}.{H}. and {R}ossi, {F}. and {C}ottrell, {G}illes and {H}ounkonnou, {M}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his work deals with prediction of anopheles number using environmental and climate variables. {T}he variables selection is performed by {GLMM} ({G}eneralized linear mixed model) combined with the {L}asso method and simple cross validation. {S}elected variables are debiased while the prediction is generated by simple {GLMM}. {F}inally, the results reveal to be qualitatively better, at selection, the prediction point of view than those obtained by the reference method.},
  keywords = {{PALUDISME} ; {VECTEUR} ; {REPARTITION} {GEOGRAPHIQUE} ; {CLIMAT} ; {GEOSTATISTIQUE} ; {REGRESSION} ; {MODELE} {PREDICTIF} ; {BENIN}},
  numero = {},
  pages = {10  multigr.},
  booktitle = {},
  year = {2013},
  URL = {https://www.documentation.ird.fr/hor/fdi:010067309},
}