fitme_body

HLfit.obj

.HLfit_body_augZXy

.solve_IRLS_as_ZX

.solve_IRLS_as_spprec

Initialize

Variogram

coef

coef&lt;-

corFactor

corMatrix

getCovariate

logDet

recalc

spaMM_Gamma

get_HLCorcall

HLCor.obj

corrHLfit_body

corrMM.LRT

getCall.HLfit

getPar

HLCor_body

HLfit_body

makeTicks

Matern.corr

niceLabels

overcat

crack

 internal

spaMM-internal

Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Both classical geostatistical models, and Markov random field models on irregular grids, can be fitted. Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.

Franois Rousset

spaMM

Mixed-Effect Models, Particularly Spatial Models

Fran<c3><a7>ois Rousset

Jean-Baptiste Ferdy

Alexandre Courtiol

GSL authors 

spaMM-internal function

Internal spaMM Functions — spaMM-internal

Internal spaMM Functions

Get 50% off unlimited learning

spaMM-internal: Internal spaMM Functions

Description

Arguments

Details