Haavard Rue

发表

A novel method of marginalisation using low discrepancy sequences for integrated nested Laplace approximations

Paul T. Brown, Chaitanya Joshi, Stephen Joe, 2019, Computational Statistics & Data Analysis.

Think continuous: Markovian Gaussian models in spatial statistics

Haavard Rue, Finn Lindgren, Daniel Simpson, 2011, 1110.6796.

Beyond the Valley of the Covariance Function

Haavard Rue, Finn Lindgren, Daniel Simpson, 2015, 1507.08383.

A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA)

Haavard Rue, Janine B. Illian, Sigrunn H. Sorbye, 2012, 1301.1817.

Unsupervised empirical Bayesian multiple testing with external covariates

Haavard Rue, Egil Ferkingstad, Arnoldo Frigessi, 2008, 0807.4658.

Approximate simulation-free Bayesian inference for multiple changepoint models with dependence within segments

Haavard Rue, Nial Friel, Jason Wyse, 2010, 1011.5038.

Constructing Priors that Penalize the Complexity of Gaussian Random Fields

Haavard Rue, Finn Lindgren, Daniel Simpson, 2015, Journal of the American Statistical Association.

Bayesian Estimation of Two-Part Joint Models for a Longitudinal Semicontinuous Biomarker and a Terminal Event with R-INLA: Interests for Cancer Clinical Trial Evaluation

Haavard Rue, Virginie Rondeau, Janet van Niekerk, 2020 .

Joint models as latent Gaussian models - not reinventing the wheel

Haavard Rue, Janet Van Niekerk, Haakon Bakka, 2019, 1901.09365.

Does non-stationary spatial data always require non-stationary random fields?

Haavard Rue, Finn Lindgren, Daniel Simpson, 2014 .

Spatial modelling with R-INLA: A review

Haavard Rue, David Bolin, Finn Lindgren, 2018, 1802.06350.

Efficient quantile tracking using an oracle

Haavard Rue, Anis Yazidi, Hugo L. Hammer, 2020, Applied Intelligence.

Quantile Tracking in Dynamically Varying Data Streams Using a Generalized Exponentially Weighted Average of Observations

Anis Yazidi, Haavard Rue, Hugo Lewi Hammer, 2019, 1901.04681.

Intuitive Joint Priors for Variance Parameters

Haavard Rue, Ingeborg Gullikstad Hem, Geir-Arne Fuglstad, 2019, Bayesian Analysis.

Using INLA to fit a complex point process model with temporally varying effects – a case study

Haavard Rue, Janine B. Illian, S Soerbye, 2012 .

Towards Continuous Domain Models in Spatial Epidemiology

Haavard Rue, Dominic Schuhmacher, Garyfallos Konstantinoudis, 2018, ISEE Conference Abstracts.

Competing risks joint models using R-INLA

Haavard Rue, Janet van Niekerk, Haakon Bakka, 2019, Statistical Modelling.

Non-stationary Gaussian models with physical barriers

Haavard Rue, Daniel Simpson, Jarno Vanhatalo, 2016, Spatial Statistics.

Unemployment estimation: Spatial point referenced methods and models

Haavard Rue, Soraia Pereira, Luis Correia, 2017, Spatial Statistics.

Estimating animal abundance with N-mixture models using the R-INLA package for R

Haavard Rue, Timothy D. Meehan, Nicole L. Michel, 2017 .

Estimating Tukey depth using incremental quantile estimators

Haavard Rue, Anis Yazidi, Hugo Lewi Hammer, 2020, Pattern Recognit..

Bayesian Computing with INLA: A Review

Haavard Rue, Daniel P. Simpson, Andrea Riebler, 2016, 1604.00860.

Estimation of Multiple Quantiles in Dynamically Varying Data Streams

Anis Yazidi, Haavard Rue, Hugo Lewi Hammer, 2017 .

Penalised Complexity Priors for Stationary Autoregressive Processes

Haavard Rue, Sigrunn Holbek Sorbye, H. Rue, 2016, 1608.08941.

Fast and accurate Bayesian model criticism and conflict diagnostics using R‐INLA

Haavard Rue, Leonhard Held, Egil Ferkingstad, 2017, 1708.03272.

Prior specification in flexible models

Haavard Rue, Maria Franco-Villoria, Massimo Ventrucci, 2019 .

A unified view on Bayesian varying coefficient models

Haavard Rue, Maria Franco-Villoria, Massimo Ventrucci, 2018, Electronic Journal of Statistics.

Bayesian Model Averaging with the Integrated Nested Laplace Approximation

Haavard Rue, Virgilio G'omez-Rubio, Roger S. Bivand, 2019, Econometrics.

A principled distance-based prior for the shape of the Weibull model

Haavard Rue, Janet van Niekerk, Haakon Bakka, 2020, Statistics & Probability Letters.

Improving Bayesian Local Spatial Models in Large Datasets

Haavard Rue, Marc G. Genton, Stefano Castruccio, 2019, J. Comput. Graph. Stat..

Practical strategies for GEV-based regression models for extremes

Haavard Rue, Raphael Huser, Daniela Castro-Camilo, 2021 .

The Bayesian Learning Rule pdf

Haavard Rue, Mohammad Emtiyaz Khan, 2021, ArXiv.

Modelling short-term precipitation extremes with the blended generalised extreme value distribution

Haavard Rue, Sara Martino, Daniela Castro-Camilo, 2021 .

Quantification of Empirical Determinacy: The Impact of Likelihood Weighting on Posterior Location and Spread in Bayesian Meta-Analysis Estimated with JAGS and INLA

Haavard Rue, Malgorzata Roos, Sona Hunanyan, 2021, Bayesian Analysis.

Joint posterior inference for latent Gaussian models with R-INLA

Haavard Rue, Janet van Niekerk, Cristian Chiuchiolo, 2021, Journal of Statistical Computation and Simulation.

The SPDE approach for Gaussian and non-Gaussian fields: 10 years and still running

Haavard Rue, David Bolin, Finn Lindgren, 2021, Spatial Statistics.

Correcting the Laplace Method with Variational Bayes pdf

Haavard Rue, Janet van Niekerk, H. Rue, 2021, ArXiv.

New Frontiers in Bayesian Modeling Using the INLA Package in R

Haavard Rue, Olaf Schenk, Janet van Niekerk, 2019, J. Stat. Softw..

Importance Sampling with the Integrated Nested Laplace Approximation

Haavard Rue, Sara Martino, Virgilio G'omez-Rubio, 2021 .

Smart Gradient - An Adaptive Technique for Improving Gradient Estimation pdf

Haavard Rue, Janet Van Niekerk, Esmail Abdul Fattah, 2021, Foundations of Data Science.

Multivariate Gaussian Random Fields with Oscillating Covariance Functions using Systems of Stochastic Partial Differential Equations

Haavard Rue, Finn Lindgren, Daniel Simpson, 2013, 1307.1384.

An approximate fractional Gaussian noise model with computational cost

Haavard Rue, Eirik Myrvoll-Nilsen, H. Rue, 2017 .

Spatial Modelling of Temperature and Humidity using Systems of Stochastic Partial Differential Equations

Haavard Rue, Daniel Simpson, Sara Martino, 2013, 1307.1402.

Model-aware Quantile Regression for Discrete Data

Haavard Rue, Tullia Padellini, H. Rue, 2018, 1804.03714.

Norges Teknisk-naturvitenskapelige Universitet Multivariate Gaussian Random Fields Using Systems of Stochastic Partial Differential Equations Multivariate Gaussian Random Fields Using Systems of Stochastic Partial Differential Equations

Haavard Rue, Finn Lindgren, Daniel Simpson, 2022 .

Bayesian Adaptive Smoothing Spline using Stochastic Differential Equations

Haavard Rue, Finn Lindgren, Daniel Simpson, 2012, 1209.2013.

Going off grid: computationally efficient inference for log-Gaussian Cox processes

Haavard Rue, Finn Lindgren, Daniel Simpson, 2016 .

Extending INLA to a class of near-Gaussian latent models

Haavard Rue, Thiago G. Martins, H. Rue, 2012, 1210.1434.

Model-based Quantile Regression for Discrete Data

Haavard Rue, Tullia Padellini, H. Rue, 2018 .

Estimation and extrapolation of time trends in registry data—Borrowing strength from related populations

Haavard Rue, Leonhard Held, Andrea Riebler, 2011, 1108.0606.