PDF | | ResearchGate, the professional network for scientists. Fits (extended) generalized linear mixed-effects models to data using a variety of distributions and link functions, including zero-inflated models. Package details. Author, Hans Skaug, Dave Fournier , Anders Nielsen, Arni.

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For now, this page is only covering “basic” mixed modeling packagr although the line is admittedly somewhat blurry: Edit History Tags Source. Create account or Sign in.

Welcome page What is a Wiki Site? How to edit pages? How to join this site? Bayesian priors can be included. Some complex variance structures heterogeneous yes, AR1 no.

Ported from S-plus to R. Nested random effects easily modeled. Crossed random effects difficult. Multiple functions lme for linear, nlme for nonlinear, gls for no random terms. Complex and custom variance structures possible.

Under active development, especially for GLMMs. No complex variance structures. Uses sparse matrix algebra, handles crossed random effects well.


Much faster than nlme. Automatic Differentiation Model Builder. Started out as a commercial product, but now open-source. It also has other features such as simpler syntax to request predictable functions of random effects.

na.action within glmmADMB package?

Multiple denominator degrees of freedom methods Glm,admb Roger, Satterthwaite, Containment. Uses sparse matrices and Average Information for speed. Widely used in plant and animal breeding. Numerous error structures supported.

The glmmADMB package

PQL only, warnings in documentation. Constraints on parameters allowed.

P This function tends to be fast and reliable, compared to competitor functions which pacmage randomized block models, when then number of observations is small, say no more than However it packqge quadratically slow as the number of observations increases because of the need to do two eigenvalue decompositions of order nearly equal to the number of observations.

So it is a good choice when fitting large numbers of small data sets, but not a good choice for fitting large data sets. Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-ShareAlike 3. WikiPlan tools for participatory design of cities. Click here to edit contents of this page. Click here to toggle editing of individual sections of the page if possible. Watch headings for an “edit” link when available.


Append content without editing the whole page source. If you want to discuss contents of this page – this is the easiest glmmaadmb to do it.

glmmADMB: Generalized Linear Mixed Models using ‘AD Model Builder’

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Wald summarylikelihood ratio test anovasequential and marginal conditional F tests anova. F statistics sans denominator df: