000 02294nam a22003737i 4500
001 AZUAY-74750
003 AZUAY
005 20251111042911.0
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020 _a978-0-387-87457-9
040 _aAZUAY
_bspa
_cAZUAY
_dAZUAY
_erda
041 0 _aeng
082 0 4 _a577.7
_bZ967
100 1 _aSmith, Graham M.,
_eautor
245 1 0 _aMixed effects models and extensions in ecology with R
250 _a1a ed.
264 3 1 _aNew York :
_bSpringer,
_c2009
300 _axxii, 574 páginas :
_bilustraciones
300 _bImpreso
336 _2rdacontent
_atexto
_btxt
337 _2rdamedia
_ano mediado
_bn
338 _2rdacarrier
_avolumen
_bnc
504 _aIncluye Referencias, Incluye indice
520 3 _bContiene: Limitations of linear regression applied on ecological data. Things are not always linear; additive modelling. Dealing with heterogeneity. Mixed effects modelling for nested data. Violation of independence. Meet the exponential family. GLM and GAM for count data. GLM and GAM for absence-presence and proportional data. Zero-truncated and zero-inflated models for count data. Generalised estimation equations. GLMM and GAMM. Estimating trends for antarctic birds in relation. Large-scale impacts of land-use change in a scottish, farming catchment. Negative binomial GAM and GAMM to analyse amphibian roadkills. Addtive mixed modelling applied on deep-sea pelagic bioluminescent organisms. Additive mixed modelling applied on phytoplankton time series data. Mixed effects modelling applied on american foulbrood affecting honey bees larvae. Three-way nested data for age determination techniques applied to cetaceans. GLMM applied on the spatial distribution of koalas in a fragmented landscape. A comparison of GLM, GEE and GLMM aplied to badger activity data. Incorporating temporal correlation in seal abundance data with MCMC. Required pre-knowledge: a linear regression and additive modelling example
650 1 4 _aBIOLOGÍA
650 1 4 _aMÉTODOS ESTADÍSTICOS
654 0 _a577.7 - Ecología marina
654 0 _a577.7 - Ecología marina
700 1 _aIeno, Elena N.,
_eautor
700 1 _aSaveliev, Anatoly,
_eautor
700 1 _aWalker, Neil J.,
_eautor
700 1 _aZuur, Alain F.,
_eautor
942 _2ddc
_c5
999 _c29514
_d29514