@article{fdi:010050502,
  title = {{A} {B}ayesian hierarchical extreme value model for lichenometry},
  author = {{C}ooley, {D}. and {N}aveau, {P}. and {J}omelli, {V}incent and {R}abatel, {A}ntoine and {G}rancher, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}urrently, there is a tremendous scientific research effort in the area of climate change. {I}n this paper, our motivation is to improve the understanding of historical climatic events such as the {L}ittle lee {A}ge ({LIA}), a period of relatively cold weather around 1450-1850 {AD}. {A}lthough the {LIA} is well documented in {E}urope, its extent and timing are not known in areas of the globe where climatological records were not kept during this period. {T}o study the climate, which predates historical records, proxy climate records must be used. {A} proxy record for the timing of climatic cooling events are the ages of the moraines left behind by glacial advances. {U}nfortunately, to determine the ages of these moraines in alpine environments there is little material available but lichens. {H}ence, lichenometry was developed to determine the ages of glacial landforms by using lichen measurements. {T}o our knowledge, this article provides the first attempt at deriving a comprehensive statistical model for lichenometry. {O}ur model foundation is based on extreme value theory because only the largest lichens are measured in lichenometry studies. {T}his application is novel to extreme value theory because the quantities of interest (the ages of climatic events) are not the measured quantities (lichen diameters), i.e., it is a inverse problem. {W}e model the lichen measurements with the generalized extreme value ({GEV}) distribution, upon which a {B}ayesian hierarchical model is built. {T}he hierarchical model enables estimation of the hidden covariate ages of the moraines. {T}he model also allows for pooling of data from different locations and evaluation of spatial differences in lichen growth. {P}arameter inference is obtained using a straightforward {M}arkov {C}hain {M}onte {C}arlo method. {O}ur procedure is applied to data gathered from the {C}ordillera {R}eal region in {B}olivia. {C}opyright (c) 2006 {J}ohn {W}iley and {S}ons, {L}td.},
  keywords = {extreme value theory ; {B}ayesian hierarchical model ; {MCMC} ; lichenometry},
  booktitle = {},
  journal = {{E}nvironmetrics},
  volume = {17},
  numero = {6},
  pages = {555--574},
  ISSN = {1180-4009},
  year = {2006},
  DOI = {10.1002/env.764},
  URL = {https://www.documentation.ird.fr/hor/fdi:010050502},
}