Cross Validated questions 365716 What does it mean when a low number of quadrature points Sep 7 2018 The value of the nAGQ parameter determines the number of quadrature points used in approximating the likelihood with 1 corresponding to a Laplace approximation and 0
bbolker github io morelia 2018 notes Generalized linear mixed models in R nitty gritty GitHub Pages Aug 5 2018 In lme4 use the nAGQ argument nAGQ 1 default corresponds to Laplace approximation
r sig mixed models r project narkive com r sig me nagq 0 R sig ME nAGQ 0 narkive I 39 m pretty sure that nAGQ 0 is generating conditional modes of group values for the random effects without subsequently using a laplace approximation This is really not
search r project org CRAN refmans Control of Mixed Model Fitting search r project org Run an initial optimization phase with nAGQ 0 While the initial optimization usually provides a good starting point for subsequent fitting thus increasing overall
angrystatistician blogspot com 2015 10 Mixed Models in R Bigger Faster Stronger Oct 4 2015 Model fitting is an optimization process Part of that process involves the estimation of particular integrals which can be very slow the option nAGQ 0 tells glmer to People also search for
Nagq Parameter
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rdrr io cran lme4 lmerControl Control of Mixed Model Fitting in lme4 Linear Jul 3 2024 Construct control structures for mixed model fitting All arguments have defaults and can be grouped into all the parameters to be passed to the optimizer e g
Cross Validated questions 544937 lme4 nlme When is it appropriate to set nAGQ 0 in glmer Sep 17 2021 According to the documentation for glmer nAGQ refers to the number of points per axis for evaluating the adaptive Gauss Hermite approximation to the log likelihood I
Nagq Parameter
RDocumentation packages lme4 glmer function RDocumentation Fit a generalized linear mixed effects model GLMM Both fixed effects and random effects are specified via the model formula control glmerControl start NULL
stat ethz ch pipermail r sig mixed models R sig ME nAGQ 0 ETH Z Only the covariance parameters theta are estimated during the nonlinear optimization step or nAGQ 1 fast slow the fixed effect estimates are further optimized
Stack Overflow questions 31634168 r argument for using nAGQ 0 in glmer lme4 Stack Overflow Jul 26 2015 I wanted to use nAGQ 1 for my cross validation but because it take a looong time per model the cross validation would take about a week which I dont have the time to