The image for each paper is an AI-generated modification of an original image in the paper.
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Time-Varying Multi-Seasonal AR Models
with Ganna Fagerberg and Robert Kohn
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Joint estimation of the predictive ability of experts using a multi-output Gaussian process
with Oscar Oelrich
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Modeling local predictive ability using power-transformed Gaussian processes
with Oscar Oelrich
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Bayesian Prediction with Covariates Subject to Detection Limits
with Caroline Svahn
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When are Bayesian model probabilities overconfident?
with Oscar Oelrich, Shutong Ding, Måns Magnusson and Aki Vehtari
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Journal Articles
Bayesian Modeling of Effective and Functional Brain Connectivity using Hierarchical Vector Autoregressions
with Bertil Wegmann, Anders Lundquist and Anders Eklund Journal of the Royal Statistical Society, Series C.(2024)
Spectral Subsampling MCMC for Stationary Multivariate Time Series with Applications to Vector ARTFIMA Processes
with Matias Quiroz, Robert Kohn and Robert Salomone Econometrics & Statistics - Part B Statistics.(2024)
Local Prediction Pools
with Oscar Oelrich and Sebastian Ankargren Journal of Forecasting(2024)
Bayesian Optimization of Hyperparameters from Noisy Marginal Likelihood Estimates
with Oskar Gustafsson and Pär Stockhammar Journal of Applied Econometrics(2023)
Dynamic Mixture of Experts Models for Online Prediction
with Parfait Munezero and Robert Kohn Technometrics(2022)
Robust Real-Time Delay Predictions in a Network of High-Frequency Urban Buses
with Hector Rodriguez-Deniz IEEE Transactions on Intelligent Transportation Systems(2022)
A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport
with Hector Rodriguez-Deniz and Augusto Voltes-Dorta Transportation Research Part C - Emerging Technologies(2022)
Spatial 3D Matérn priors for fast whole-brain fMRI analysis
with Per Sidén, Finn Lindgren, David Bolin and Anders Eklund Bayesian Analysis(2021)
The block-Poisson estimator for optimally tuned exact subsampling MCMC
with Matias Quiroz, Minh-Ngoc Tran, Robert Kohn and Khue-Dung Dang Journal of Computational and Graphical Statistics(2021)
Physiological Gaussian Process Priors for the Hemodynamics in fMRI Analysis
with Josef Wilzén and Anders Eklund Journal of Neuroscience Methods(2020)
DOLDA - a regularized supervised topic model for high-dimensional multi-class regression
with Måns Magnusson and Leif Jonsson Computational Statistics(2020)
Hamiltonian Monte Carlo with Energy Conserving Subsampling
with Khue-Dung Dang, Matias Quiroz, Robert Kohn and Minh-Ngoc Tran Journal of Machine Learning Research(2019)
Speeding Up MCMC by Efficient Data Subsampling
with Matias Quiroz, Robert Kohn and Minh Ngoc Tran Journal of the American Statistical Association(2019)
Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models
with Måns Magnusson, Leif Jonsson and David Broman Journal of Computational and Graphical Statistics(2019)
Speeding Up MCMC by Delayed Acceptance and Data Subsampling
with Matias Quiroz, Minh Ngoc Tran and Robert Kohn Journal of Computational and Graphical Statistics(2019)
Efficient Covariance Approximations for Large Sparse Precision Matrices
with Per Sidén, Finn Lindgren and David Bolin Journal of Computational and Graphical Statistics(2018)
Tree Ensembles with Rule Structured Horseshoe Regularization
with Malte Nalenz Annals of Applied Statistics(2018)
Subsampling MCMC - An Introduction for the Survey Statistician
with Matias Quiroz, Robert Kohn, Minh-Ngoc Tran and Khue-Dung Dang Sankhya A(2018)
Invited discussion of “Bayesian Spatiotemporal Modeling Using Hierarchical Spatial Priors, with Applications to fMRI”
with Per Sidén Bayesian Analysis(2018)
Fast Bayesian Whole-Brain fMRI Analysis with Spatial 3D Priors
with Per Sidén, Anders Eklund and David Bolin NeuroImage(2017)
A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes
with Anders Eklund and Martin A. Lindquist NeuroImage(2017)
Bayesian Rician Regression for Neuroimaging
with Bertil Wegmann and Anders Eklund Frontiers in Neuroscience(2017)
BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs
with Anders Eklund, Paul Dufort and Stephen LaConte Frontiers in Neuroinformatics(2014)
Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios
with Paolo Giordani, Tor Jacobson and Erik von Schedvin Journal of Financial and Quantitative Analysis(2014)
Harnessing Graphics Processing Units for Improved Neuroimaging Statistics
with Anders Eklund and Stephen LaConte Cognitive, Affective, & Behavioral Neuroscience(2013)
Efficient Bayesian Multivariate Surface Regression
with Feng Li Scandinavian Journal of Statistics(2013)
Regression Density Estimation With Variational Methods and Stochastic Approximation
with David Nott, Siew Li Tan and Robert Kohn Journal of Computational and Graphical Statistics(2012)
Generalized Smooth Finite Mixtures
with David Nott and Robert Kohn Journal of Econometrics(2012)
Bayesian Inference in Structural Second-Price Common Value Auctions
with Bertil Wegmann Journal of Business and Economic Statistics(2011)
Flexible Modeling of Conditional Distributions using Smooth Mixtures of Asymmetric Student t Densities
with Feng Li and Robert Kohn Journal of Statistical Planning and Inference(2010)
Forecasting Macroeconomic Time Series with Locally Adaptive Signal Extraction
with Feng Li and Robert Kohn International Journal of Forecasting(2010)
Steady-State Priors for Vector Autoregressions
with Mattias Villani Journal of Applied Econometrics(2009)
Regression Density Estimation using Smooth Adaptive Gaussian Mixtures
with Robert Kohn and Paolo Giordani Journal of Econometrics(2009)
Evaluating an Estimated New Keynesian Small Open Economy Model
with Malin Adolfson, Stefan Laséen and Jesper Lindé Journal of Economic Dynamics and Control(2008)
Empirical Properties of Closed and Open Economy DSGE Models of the Euro Area
with Malin Adolfson, Stefan Laséen and Jesper Lindé Macroeconomic Dynamics(2008)
Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks
with Malin Adolfson, Michael K. Andersson, Jesper Lindé and Anders Vredin International Journal of Central Banking(2007)
Bayesian Estimation of an Open Economy DSGE Model with Incomplete Pass-Through
with Malin Adolfson, Stefan Laséen and Jesper Lindé Journal of International Economics(2007)
Bayesian Analysis of DSGE Models — Some Comments
with Malin Adolfson and Jesper Lindé Econometric Reviews(2007)
Forecasting Performance of an Open Economy DSGE Model
with Malin Adolfson and Jesper Lindé Econometric Reviews(2007)
Bayesian Point Estimation of the Cointegration Space
with Mattias Villani Journal of Econometrics(2006)
The Multivariate Split Normal Distribution and Asymmetric Principal Components Analysis
with Rolf Larsson Communications in Statistics - Theory and Methods(2006)
A Bayesian Approach to Modelling Graphical Vector Autoregressions
with Jukka Corander Journal of Time Series Analysis(2006)
The Role of Sticky Prices in an Open Economy Dsge Model: A Bayesian Investigation
with Malin Adolfson, Stefan Laséen and Jesper Lindé Journal of the European Economic Association(2005)
Are Constant Interest Rate Forecasts Modest Policy Interventions? Evidence from a Dynamic Open-Economy Model
with Malin Adolfson, Stefan Laséen and Jesper Lindé International Finance(2005)
Bayesian Reference Analysis of Cointegration
with Mattias Villani Econometric Theory(2005)
Bayesian Assessment of Dimensionality in Reduced Rank Regression
with Jukka Corander Statistica Neerlandica(2005)
Bayesian Prediction with Cointegrated Vector Autoregressions
with Mattias Villani International Journal of Forecasting(2001)
Fractional Bayesian Lag Length Inference in Multivariate Autoregressive Processes
with Mattias Villani Journal of Time Series Analysis(2001)
A Distance Measure Between Cointegration Spaces
with Rolf Larsson Economics Letters(2001)
Refereed Conference Proceedings
Spectral Subsampling MCMC for Stationary Time Series
with Robert Salomone, Matias Quiroz, Robert Kohn and Minh-Ngoc Tran International Conference on Machine Learning (ICML)(2020)
Anatomically Informed Bayesian Spatial Priors for fMRI analysis
with David Abramian, Per Sidén, Hans Knutsson and Anders Eklund IEEE International Symposium on Biomedical Imaging (ISBI)(2020)
Real-Time Robotic Search using Hierarchical Spatial Point Processes
with Olov Andersson, Per Sidén, Johan Dahlin and Patrick Doherty Uncertainty in Artificial Intelligence (UAI)(2019)
Urban Network Travel Time Prediction via Online Multi-Output Gaussian Process Regression
with Hector Rodriguez-Deniz and Erik Jenelius IEEE International Conference on Intelligent Transportation Systems (ITSC)(2017)
Bayesian Diffusion Tensor Estimation with Spatial Priors
with Xuan Gu, Per Sidén, Bertil Wegmann, Anders Eklund and Hans Knutsson Computer Analysis of Images and Patterns (CAIP)(2017)
Intrusion-Damage Assessment and Mitigation in Cyber-Physical Systems for Control Applications
with Rouhollah Mahfouzi, Amir Aminifar, Petru Eles, and Zebo Peng International Conference on Real-Time Networks and Systems (RTNS)(2016)
Automatic Localization of Bugs to Faulty Components in Large Scale Software Systems Using Bayesian Classification
with Leif Jonsson, David Broman, Måns Magnusson, Kristian Sandahl and Sigrid Eldh IEEE International Conference on Software Quality, Reliability and Security (QRS)(2016)
Perception-Aware Power Management for Mobile Games via Dynamic Resolution Scaling
with Arian Maghazeh, Unmesh D. Bordoloi, Petru Eles and Zebo Peng IEEE/ACM International Conference on Computer-Aided Design (ICCAD)(2015)
Statistical Analysis of Process Variation based on Indirect Measurements for Electronic System Design
with Ivan Ukhov, Petru Eles and Zebo Peng IEEE/ACM ASP-DAC Design Automation Conference(2014)
Book Chapters
Bayesian Heteroscedastic Regression for Diffusion Tensor Imaging
with Bertil Wegmann and Anders Eklund In 'Modeling, Analysis, and Visualization of Anisotropy' (Schultz, Özarslan and Hotz eds.), Springer(2017)
Modelling Conditional Densities Using Finite Smooth Mixtures
with Feng Li and Robert Kohn In 'Mixture models - Estimation and Applications (Robert, Mengerson and Titterington, eds), Wiley(2011)
Bayesian Approaches to Cointegration
with Gary Koop, Rodney Strachan and Herman van Dijk In 'Palgrave Handbook of Econometrics, Vol 1, Econometric Theory'(2006)
Books
Official Statistics – Methodology and Applications in Honour of Daniel Thorburn
with Michael Carlson and Hans Nyquist (editors) (2006)
Other publications
The Riksbank’s communication of macroeconomic uncertainty
with David Kjellberg Sveriges Riksbank Economic Review(2010)
RAMSES – a new general equilibrium model for monetary policy analysis
with Malin Adolfson, Stefan Laseén and Jesper Lindé Sveriges Riksbank Economic Review(2007)
Aspects of Bayesian Cointegration
with Mattias Villani PhD thesis in Statistics, Stockholm University(2007)
Older working papers
Modeling Text Complexity using a Multi-Scale Probit
with Johan Falkenjack and Arne Jönsson (2018)
The Block Pseudo-Marginal Sampler
with Minh-Ngoc Tran, Robert Kohn and Matias Quiroz (2017)
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
with Johan Dahlin and Thomas Schön (2015)
Monetary Policy Analysis in a Small Open Economy Using Bayesian Cointegrated Structural VARs
with Anders Warne (2014)
Dynamic Mixture-of-Experts Models for Longitudinal and Discrete-Time Survival Data
with Matias Quiroz (2013)
Bayesian Inference of General Linear Restrictions on the Cointegration Space
with Mattias Villani (2005)
Panel Regression with Unobserved Classes
with Mickael Bäckman (2000)
