The key operation in Bayesian inference is to compute high-dimensional integrals. An old
approximate technique is the Laplace method or approximation, which dates back to Pierre …

Social network analysis has achieved remarkable popularity in disease ecology, and is
sometimes carried out without investigating spatial heterogeneity. Many investigations into …

The INLA approach for approximate Bayesian inference for latent Gaussian models has
been shown to give fast and accurate estimates of posterior marginals and also to be a …

Inbreeding depression is ubiquitous, but we still know little about its genetic architecture and
precise effects in wild populations. Here, we combine long-term life-history data with 417 K …

Estimating heritability of traits in wild populations is a major prerequisite to understand their
evolution. Until recently, most heritability estimates had been obtained using parent …

Understanding and reducing the incidence of accidental bycatch, particularly for vulnerable
species such as sharks, is a major challenge for contemporary fisheries management. Here …

This is a short description and basic introduction to the Integrated nested Laplace
approximations (INLA) approach. INLA is a deterministic paradigm for Bayesian inference in …

Objective Obesity is a major risk factor for multiple diseases and is in part heritable, yet the
majority of causative genetic variants that drive excessive adiposity remain unknown. Here …

The structure of wild animal social systems depends on a complex combination of intrinsic
and extrinsic drivers. Population structuring and spatial behaviour are key determinants of …

Motivation Genomic sequencing studies, including RNA sequencing and bisulfite
sequencing studies, are becoming increasingly common and increasingly large. Large …