From e23f053697cfdaa2fae092b39d821e8876e7e6e0 Mon Sep 17 00:00:00 2001 From: Seb Dalgarno Date: Tue, 30 Apr 2024 10:44:58 -0700 Subject: [PATCH] add LA ref back in --- vignettes/articles/methods.Rmd | 1 + 1 file changed, 1 insertion(+) diff --git a/vignettes/articles/methods.Rmd b/vignettes/articles/methods.Rmd index 68fcf86..9b63e91 100644 --- a/vignettes/articles/methods.Rmd +++ b/vignettes/articles/methods.Rmd @@ -41,6 +41,7 @@ Fixed and random effects can be used in Bayesian or frequentist models. The frequentist approach simply identifies the parameter values that maximize the likelihood, i.e., have the greatest probability of having produced the data if they were true. It does this by searching parameter space for the combination of parameter values with the Maximum Likelihood. +Parameter estimates for random effects can be estimated using the Laplace approximation (i.e., with software packages [TMB](https://arxiv.org/pdf/1509.00660.pdf) or [Nimble](https://r-nimble.org/html_manual/cha-AD.html#how-to-use-laplace-approximation)). The CIs are calculated using the standard errors, assuming that the likelihood is normally distributed. This approach has the advantage of being fast.