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Methods

Implementation notes for custom latent models, custom likelihoods, and smoothers in R-INLA.

MMM goes bru: how to implement the hill(adstock(-)) function from Meridian in inlabru?

I was recently looking at the Marketing Mix Modelling literature, which is essentially Bayesian probabilistic modelling applied to marketing and adjacent business questions.…

Another look at DLNM with inlabru

This methods note will take another look at distributed lag non-linear models with inlabru. More specifically, I’ll show how to specify the model using the _eval features.

Fitting Bayesian Distributed Lag Non-Linear Models with inlabru

Distributed lag non-linear models (DLNMs) are useful when an exposure can affect the response both non-linearly and with a delay. A common example is environmental…

MMD estimator

Download inla_mmd_cloglike.c

Censored binomial likelihood in R-INLA

Download cloglike-censored-binomial.c

Univariate P-splines in R-INLA and inlabru

P-splines combine a flexible B-spline basis with a roughness penalty on the coefficients. Their main practical objective is to make model specification more robust to the…

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Olivier Supplisson (2026).