Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [inla]

Integrated Nested Laplace Approximation

A method for approximate inference on Bayesian hierarchical models.

18 questions
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Is there an R package for MCMC estimation of Generalized Method of Moments?

I'm looking for an R package (or a combination of packages) that would allow me to perform MCMC estimation of a GMM model, with a user-specified moments function. I've looked at the CRAN Bayesian task-view, but I can't seem to find what I'm looking…
jubo
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How to specify the unit information prior

Continuing on from this question and this question re BIC and its approximation to the Bayes factor with a unit information prior (Kass & Wasserman, 1995), I'm trying to quantify this relationship as a stepping stone into Bayesian stats. So far, my…
Matt Albrecht
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Who invented INLA?

I am trying to do a literature review on integrated nested Laplace approximations (INLA). Most papers cite a popular paper by Rue and Chopin, however, this does not seem to be the seminal paper. Can anyone point me to the roots of this method?
HeMan
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How to model spatial data using SPDE and finite element method

Suppose we want to model a stochastic process using Gaussian processes. We have data on $z$ (dependent variable) at some spatial points $(x_{i},y_{i})$. If our dataset is large then calculating the covariance matrix of the Gaussian process becomes…
Amin Shn
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How to validate or make predictions from a spatial Cox PH survival model built with R-INLA?

I'm trying to model deforestation as a survival analysis. I have a raster map where unaffected areas are zero and deforested pixels have values 1-20 depending on the year of deforestation (2001-20). I take 10km square grids as 'individuals' and…
Michael Smith
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INLA Fitting logistic regression using bym or besag smoothing using neighboring spatial points instead of neighboring polygons

Ordinarily, if you want to account for the effect spatial boundaries have on certain variables. You could fit as follows as highlighted in Virgilio Gómez-Rubio's Bayesian inference with INLA article. library("rgdal") boston.tr <-…
ccc
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Bayesian spatial autoregressive (SAR) model with heteroskedasticity in R

In socio-economic data, I always found heteroskedasticity that can't be solved using transformation.I had read a paper "Spatial autoregressive models with unknown heteroskedasticity:A comparison of Bayesian and robust GMM approach". In this paper, I…
Fitri Ramadhini
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How can I interpret the estimated random coefficients (e.g. random intercept) in a mixed model?

We know that random effects are estimated as a probability distribution rather than each individual random coefficients. Take the simplest random intercept model as an example: $biomass_{i,j}$ ~ $treatment_{i,j}$ + $site_{i}$, $site_{i}$~$N(0,…
tiantianchen
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What means that the model is "singular"?

My question might be rather basic, theoretical. I am running spatial and spatial-temporal bayesian models in INLA. I have areal data and a continuous response variable with spatial and temporal dependencies. I've got error messages during model…
marina_esp
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Can we use INLA for the following model?

Suppose that we have the following model $$Y_{i}\sim Pois(N_{j}e^{x})$$ $$N_{j}\sim Pois(\xi_{j})$$ $$log(\xi_{j})= a+bz_{j} + \epsilon_{j}$$ With $i=1,...I, j=1,...,J$ where $x$ is a random parameter and $z_{j}$ covariates, and $\epsilon_{j}\sim…
Fiodor1234
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INLA model with spatial autocorrelation - binary response, binomial predictor

I have a binary response variable (0/1) and a predictor distributed continuously on 0-1 scale. There is significant spatial autocorrelation in data, thus I am running an INLA model to account for that. I created a reproducible example that also…
MIH
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Setting priors for a beta distribution in R-INLA

I'm running a regression in R-INLA, where the response variable is proportion of grid squares suffering deforestation (by year, over a 20-year period). Setting the response for the last 5 years to NA and re-running the model fit (which is the…
Michael Smith
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Variable selection in Bayesian hierarchical models with R-INLA

I'm working with Bayesian hierarchichal regressions fitted with R-INLA. I would like to simplify my model by reducing the number of covariates. According to my understanding, Bayesian variable selection (spike & slab priors) cannot be done with…
antarctica
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Spatial modelling of sparse count data

I am trying to model claim counts over for a given region. The data is very sparse. I am using the BESAG model from R INLA package. I am having a tough time to model the data. I am able to reproduce my issue (to some extent) by some synthetic data…
user27396
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Model comparison: WAIC value is large between nested random effect models

I have computed two models using INLA and following the proceedure laid out in this paper. As in the paper, the model has two random effects, one representing temporal relationships between data points, and one representing spatial relationships.…
SamPassmore
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