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1. Gaussian Markov random fields
: theory and applications
by Rue, Håvard and Held, Leonhard
2005, Monographs on statistics and applied probability (Series), ISBN 9781584884323, Volume 104, 263
Gaussian Markov random fields | Statistical Theory & Methods | Statistical Computing | Geostatistics
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2. Full Text Bayesian spatial modelling with R-INLA
by Lindgren, Finn and Rue, Håvard
Journal of statistical software, ISSN 1548-7660, 2015, Volume 63, Issue 19, pp. 1 - 25
Gaussian Markov random _elds | Stochastic partial differential equations | Bayesian inference | Laplace approximation | Statistics & Probability | Physical Sciences | Computer Science, Interdisciplinary Applications | Technology | Computer Science | Mathematics | Science & Technology
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3. Full Text Bayesian computing with INLA: New features
by Martins, Thiago G and Simpson, Daniel and Lindgren, Finn and Rue, Håvard
Computational statistics & data analysis, ISSN 0167-9473, 11/2013, Volume 67, pp. 68 - 83
INLA | Latent Gaussian models | Approximate Bayesian inference | Approximate | Bayesian inference | Statistics & Probability | Physical Sciences | Computer Science, Interdisciplinary Applications | Technology | Computer Science | Mathematics | Science & Technology | Approximation
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4. Full Text Bayesian inference for generalized linear mixed models
by Fong, Youyi and Rue, Håvard and Wakefield, Jon
Biostatistics (Oxford, England), ISSN 1465-4644, 07/2010, Volume 11, Issue 3, pp. 397 - 412
Longitudinal data | Prior specification | Penalized quasi-likelihood | Spline models | Integrated nested Laplace approximations | Statistics & Probability | Physical Sciences | Mathematics | Life Sciences & Biomedicine | Science & Technology | Mathematical & Computational Biology | Stochastic Processes | Computer Simulation | Humans | Bayes Theorem | Seizures - drug therapy | Epilepsy - drug therapy | Female | Linear Models | Longitudinal Studies | Breast Neoplasms - epidemiology | Cohort Studies | Biostatistics | Approximation | Laplace transforms | Bayesian analysis | Generalized linear models | Index Medicus
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5. Full Text Bayesian penalized spline models for the analysis of spatio‐temporal count data
by Bauer, Cici and Wakefield, Jon and Rue, Håvard and Self, Steve and Feng, Zijian and Wang, Yu
Statistics in medicine, ISSN 0277-6715, 05/2016, Volume 35, Issue 11, pp. 1848 - 1865
Bayesian spatio‐temporal analysis | INLA | surveillance count data | penalized splines | Gaussian Markov random field | infectious diseases | Bayesian spatio-temporal analysis | Surveillance count data | Infectious diseases | Penalized splines | Statistics & Probability | Physical Sciences | Life Sciences & Biomedicine | Medical Informatics | Public, Environmental & Occupational Health | Mathematics | Medicine, Research & Experimental | Science & Technology | Mathematical & Computational Biology | Research & Experimental Medicine | Markov Chains | Humans | Risk Factors | Male | China - epidemiology | Disease Outbreaks | Computer Simulation | Bayes Theorem | Hand, Foot and Mouth Disease - epidemiology | Female | Poisson Distribution | Child | Population Surveillance | Mathematical models | Markov analysis | Simulation | Bayesian analysis | Public health | Index Medicus
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6. Full Text Joint Tracking of Multiple Quantiles Through Conditional Quantiles
by Hammer, Hugo Lewi and Yazidi, Anis and Rue, Håvard
Information sciences, ISSN 0020-0255, 02/2021
Data Mining | Joint Estimates | Real Time Analytics | Quantile Tracking | Data Stream
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7. Full Text Tracking of multiple quantiles in dynamically varying data streams
by Hammer, Hugo Lewi and Yazidi, Anis and Rue, Håvard
Pattern analysis and applications : PAA, ISSN 1433-7541, 2019, Volume 23, Issue 1, pp. 225 - 237
Incremental algorithm | Quantile tracking | Multiple quantiles | Dynamic environment | Computer Science, Artificial Intelligence | Technology | Computer Science | Science & Technology | Data transmission | Quantiles | Tracking | Iterative methods | Incremental algorithms | Dynamic environments
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8. Full Text A new quantile tracking algorithm using a generalized exponentially weighted average of observations
by Hammer, Hugo Lewi and Hammer, Hugo Lewi and Yazidi, Anis and Yazidi, Anis and Rue, Håvard and Rue, Håvard
Applied intelligence (Dordrecht, Netherlands), ISSN 0924-669X, 4/2019, Volume 49, Issue 4, pp. 1406 - 1420
Data stream | Artificial Intelligence | Computer Science | Concept drift detection | Generalized exponentially weighted average | Quantile tracking | Mechanical Engineering | Manufacturing, Machines, Tools, Processes | Computer Science, Artificial Intelligence | Technology | Science & Technology | Usage | Algorithms | Analysis | Detectors | Machine learning | Data transmission | State of the art | Quantiles | Tracking | Regression analysis
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9. Full Text Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
by Daniel Simpson and Håvard Rue and Andrea Riebler and Thiago G. Martins and Sigrunn H. Sørbye
Statistical science, ISSN 0883-4237, 2/2017, Volume 32, Issue 1, pp. 1 - 28
Information geometry | Prior on correlation matrices | Interpretable prior distributions | Disease mapping | Bayesian theory | Hierarchical models | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Probability distribution | Data models | Statistics | Bayesian analysis | Complexity | interpretable prior distributions | VDP | information geometry | hierarchical models | Matematikk og Naturvitenskap: 400 | Mathematics and natural science: 400 | Mathematics: 410 | disease mapping | prior on correlation matrices | Matematikk: 410
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10. Full Text Penalised Complexity Priors for Stationary Autoregressive Processes
by Sørbye, Sigrunn Holbek and Rue, Håvard
Journal of time series analysis, ISSN 0143-9782, 11/2017, Volume 38, Issue 6, pp. 923 - 935
robustness.JEL. C11; C18; C22; C88 | AR(p) | R‐INLA | prior selection | latent Gaussian models | R-INLA | Mathematics, Interdisciplinary Applications | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Formulations | Computer simulation | Time series analysis | Time series | Prior knowledge | Complexity | Personal computers | Simulation | Approaches | Robustness | Deviation | Bayesian analysis | Autoregressive processes | C22 | C88 | VDP | AR( p) | C18 | Matematikk og Naturvitenskap: 400 | Mathematics and natural science: 400 | robustness. JEL. C11 | Mathematics: 410 | Matematikk: 410
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11. Full Text An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach [with Discussion]
by Finn Lindgren and Håvard Rue and Johan Lindström and John T. Kent and Peter J. Diggle and J. B. Illian and D. P. Simpson and Tilmann Gneiting and Michael Scheuerer and R. Furrer and E. Furrer and D. Nychka and Paul Fearnhead and Peter Challenor and Yiannis Andrianakis and Gemma Stephenson and Jesper Møller and Xiangping Hu and Daniel Simpson and David Bolin and Patrick E. Brown and Michela Cameletti and Sara Martino and Daniel Cooley and Jennifer A. Hoeting and Rosa M. Crujeiras and Andrés Prieto and Marco A. R. Ferreira and Geir-Arne Fuglstad and Andrew Gelman and Peter Guttorp and Barnali Das and Ben Haaland and David J. Nott and John Haslett and Chaitanya Joshi and Vincent Garreta and Michael Höhle and L. Ippoliti and R. J. Martin and R. J. Bhansali and Venkata K. Jandhyala and Stergios B. Fotopoulos and Mikyoung Jun and Håvard Wahl Kongsgård and Giovanna Jona Lasinio and Alessio Pollice and Chihoon Lee and Wayne T. Lee and Cari G. Kaufman and Bo Li and Marc G. Genton and Georg Lindgren and K. V. Mardia and Jorge Mateu and Debashis Mondal and Werner G. Müller and Helmut Waldl and Alessandro Ottavi and Omiros Papaspiliopoulos and Emilio Porcu and Marc Saez and Alexandra M. Schmidt and Alfred Stein and Paul Switzer and Kamil Turkman and Christopher K. Wikle and Mevin B. Hooten
Journal of the Royal Statistical Society. Series B, Statistical methodology, ISSN 1369-7412, 9/2011, Volume 73, Issue 4, pp. 423 - 498
Triangulation | Approximation | Covariance | Partial differential equations | Mathematical functions | Markov models | Spatial models | Covariance matrices | Parametric models | Modeling | Latent Gaussian models | Stochastic partial differential equations | Covariance functions | Gaussian fields | Approximate Bayesian inference | Gaussian Markov random fields | Sparse matrices | Gaussian markov random fields | Approximate bayesian inference | Latent gaussian models | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Stochastic analysis | General topics | Inference from stochastic processes; time series analysis | Stochastic processes | Exact sciences and technology | Probability theory and stochastic processes | Probability and statistics | Statistics | Sciences and techniques of general use | Markov processes | Usage | Models | Algorithms | Analysis | Studies | Statistical methods | Bayesian analysis | Geostatistics | Parametrization | Computation | Mathematical analysis | Images | Mathematical models | Gaussian | Stochasticity | Naturvetenskap | Natural Sciences | Matematik | Sannolikhetsteori och statistik | Probability Theory and Statistics
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12. Full Text Bayesian bivariate meta‐analysis of diagnostic test studies with interpretable priors
by Guo, Jingyi and Riebler, Andrea and Rue, Håvard
Statistics in medicine, ISSN 0277-6715, 08/2017, Volume 36, Issue 19, pp. 3039 - 3058
penalised complexity priors | integrated nested Laplace approximation (INLA) | prior distributions | bivariate random effects model | diagnostic meta‐analysis | diagnostic meta-analysis | Statistics & Probability | Physical Sciences | Life Sciences & Biomedicine | Medical Informatics | Public, Environmental & Occupational Health | Mathematics | Medicine, Research & Experimental | Science & Technology | Mathematical & Computational Biology | Research & Experimental Medicine | Diagnostic Tests, Routine | Meta-Analysis as Topic | Urinary Bladder Neoplasms - genetics | Urinary Bladder Neoplasms - diagnosis | Bias | Computer Simulation | Humans | Sensitivity and Specificity | Bayes Theorem | Biometry - methods | Telomere | Medical tests | Analysis | Medical statistics | Bayesian analysis | Diagnostic tests | Meta-analysis | Index Medicus
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13. Full Text Beyond the Valley of the Covariance Function
by Daniel Simpson and Finn Lindgren and Håvard Rue
Statistical science, ISSN 0883-4237, 5/2015, Volume 30, Issue 2, pp. 164 - 166
Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Statistics - Methodology
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14. Full Text ESTIMATION AND EXTRAPOLATION OF TIME TRENDS IN REGISTRY DATA—BORROWING STRENGTH FROM RELATED POPULATIONS
by Andrea Riebler and Leonhard Held and Håvard Rue
The annals of applied statistics, ISSN 1932-6157, 3/2012, Volume 6, Issue 1, pp. 304 - 333
Mortality | Random walk | Chronic obstructive pulmonary disease | Cantons | Modeling | Cohort effect | Parametric models | Age | Age groups | Forecasting models | INLA | Multivariate age-period-cohort model | Uniform correlation matrix | Projections | Bayesian analysis | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Statistics - Applications | projections | multivariate age-period-cohort model | uniform correlation matrix
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