THIS PAGE IS NOT UP TO DATE.... (March 6, 2012).
In this page papers and reports using the INLA methodology are collected:
- Fong Y., Rue H. and Wakefield J., Bayesian inference for Generalized Linear Mixed Models. Biostatistics, 11, 397-412. (R-code and supplementary material)
- Martino S., Akerkar R. and Rue H., Approximate Bayesian Inference for Survival Models. (R-Code). DOI: 10.1111/j.1467-9469.2010.00715.x
- Paul M., Riebler A., Bachmann L., Rue H. and Held L., Bayesian bivariate meta-analysis of diagnostic test studies using integrated nested Laplace approximations. Statistics in Medicine, 29, 1325-1339.
- Schrö̈dle B. and Held L., A primer on disease mapping and ecological regression using INLA. Computational Statistics. DOI: 10.1007/s00180- 010-0208-2. Updated version of the supplementary material.
- Schrö̈dle B. and Held L., Spatio-temporal disease mapping using INLA. Environmetrics. DOI: 10.1002/env.1065.
- Riebler A., Held L. and Rue H., Estimation and extrapolation of time trends in registry data - Borrowing strength from related populations. Annals of Applied Statistics. Accepted. (Revised version of "Correlated multivariate age-period-cohort models").
- Riebler A., Held L., Rue H. and Bopp, M., Gender-specific differences and the impact of family integration on time trends in age-stratified Swiss suicide rates, Journal of the Royal Statistical Society, Series A. In press.
- Roos M. and Held L., Sensitivity analysis in Bayesian generalized linear mixed models for binary data, Bayesian Analysis, 6, 259-278.
- Schrödle B., Held L., Riebler A. and Danuser J., Using INLA for the evaluation of veterinary surveillance data from Switzerland: A case study. Journal of the Royal Statistical Society, Series C, 60, 261-279.
- Abellan J.J., Abellan C. and Gonzalez J.R., A Bayesian shared component model for genetic association studies. (R-code).
- Akerkar R., Martino S. and Rue H. Implementing approximate Bayesian inference for survival analysis using integrated nested Laplace approximations.
- Baghishani H., Rue H. and Mohammadzadeh M., On a hybrid data cloning method and its application in
generalized linear mixed models. (Revised version and R-code.)
- Eidsvik J., Finley A.O., Banerjee S. and Rue H., Approximate Bayesian Inference for Large Spatial Datasets Using Predictive Process Models. (Revised version.)
- Gonzalez J.R., Abellan C. and Abellan J.J., A Bayesian share component model to analyze copy number data in genetic studies.
- Illian J.B. and Rue H., A toolbox for fitting complex spatial point process models using integrated Laplace transformation (INLA). Improved submitted version.
- Illian J.B., Sørbye S.H., Rue H. and Hendrichsen D., Fitting a log Gaussian Cox process with temporally varying effects -- a case study.
- Li Y., Brown P., Rue H., Al-Maini M.
and Fortin P., Spatial modelling of Lupus incidence over 40 years with changes in
census areas. (Revised version.)
- Lindgren F., Lindstrøm J. and Rue H., An explicit link between Gaussian fields and Gaussian Markov random fields: The SPDE approach. Submitted version is here (slight changes). Revised version January 2011
- Ruiz-Cardenas R. and Krainski E.T.,
Evaluating Spatio-temporal models for crop yield forecasting using
INLA: implications to pricing are yield crop insurance contracts.
- Ruiz-Cardenas R., Krainski E.T. and Rue H., Fitting dynamic models using integrated nested Laplace approximations -- INLA. Old R-code. (Revised version and R-code.) [Link to the final version in print.]
- Simpson D., Lindgren F. and Rue H., In order to make spatial statistics computationally feasible, we need to forget about the covariance function.
- Sørbye S.H . and Rue H., Simultaneous credible bands for latent Gaussian models. (Printed article in Scandinavian Journal of Statistics.)
- Wyse J., Friel N. and Rue H., Approximate simulation free multiple changepoint analysis with Gaussian Markov random field segment models. (Revised version)
- Laurini M. and Hotta L.K., Forecasting the Term Structure of Interest Rates Using Integrated Nested Laplace Approximations.
- Schrödle B., Held L. and Rue H., Assessing the impact of network data on the spatio-temporal spread of infectious diseases. Supplementary material
- Simpson D., Lindgren, F. and Rue H., Fast approximate inference with INLA: the past, the present and the future. Technical report at arxiv.org
- Simpson D., Lindgren F. and Rue H., Think continuous: Markovian Gaussian models in spatial statistics. NTNU Technical report 9/2011.
- Simpson D,. Illian J., Lindgren F., Sørbye S.H. and Rue H, Going off grid: Computationally efficient inference for log-Gaussian Cox processes. NTNU Technical report 10/2011. (Old R-code, New R-code in SPDE Tutorial, Significantly updated version)
Cameletti M., Lindgren F., Simpson D. and Rue H., Spatio-temporal modeling of particulate matter concentration through the SPDE approach. Submitted, 2011.
- Bisanzio D., et al. Spatio-temporal patterns of distribution of West Nile virus vectors in eastern Piedmont Region, Italy, in press, 2011.