{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T10:15:59Z","timestamp":1773310559568,"version":"3.50.1"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T00:00:00Z","timestamp":1671840000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T00:00:00Z","timestamp":1671840000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"SNF SINERGIA","award":["CRSII5_189942"],"award-info":[{"award-number":["CRSII5_189942"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Stat Comput"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s11222-022-10192-1","type":"journal-article","created":{"date-parts":[[2022,12,24]],"date-time":"2022-12-24T06:02:38Z","timestamp":1671861758000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Parallelized integrated nested Laplace approximations for fast Bayesian inference"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7586-2727","authenticated-orcid":false,"given":"Lisa","family":"Gaedke-Merzh\u00e4user","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4334-2057","authenticated-orcid":false,"given":"Janet","family":"van Niekerk","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8636-1023","authenticated-orcid":false,"given":"Olaf","family":"Schenk","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0222-1881","authenticated-orcid":false,"given":"H\u00e5vard","family":"Rue","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,24]]},"reference":[{"issue":"10","key":"10192_CR1","doi-asserted-by":"publisher","first-page":"2645","DOI":"10.1007\/s00477-017-1383-2","volume":"31","author":"MW Arisido","year":"2017","unstructured":"Arisido, M.W., Gaetan, C., Zanchettin, D., Rubino, A.: A Bayesian hierarchical approach for spatial analysis of climate model bias in multi-model ensembles. Stoch. Environ. Res. Risk Assess. 31(10), 2645\u20132657 (2017). https:\/\/doi.org\/10.1007\/s00477-017-1383-2","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"10192_CR2","doi-asserted-by":"publisher","unstructured":"Ascher, U.M., Greif, C.: A first course on numerical methods. SIAM (2011). https:\/\/doi.org\/10.1137\/9780898719987","DOI":"10.1137\/9780898719987"},{"key":"10192_CR3","doi-asserted-by":"publisher","unstructured":"Atkinson, A.C., Riani, M., Riani, M.: Robust diagnostic regression analysis, Volume 2. Springer (2000). https:\/\/doi.org\/10.1007\/978-1-4612-1160-0","DOI":"10.1007\/978-1-4612-1160-0"},{"issue":"6","key":"10192_CR4","doi-asserted-by":"publisher","first-page":"e1443","DOI":"10.1002\/wics.1443","volume":"10","author":"H Bakka","year":"2018","unstructured":"Bakka, H., Rue, H., Fuglstad, G.A., Riebler, A., Bolin, D., Illian, J., Krainski, E., Simpson, D., Lindgren, F.: Spatial modelling with R-INLA: a review. WIREs Comput. Stat. 10(6), e1443 (2018). https:\/\/doi.org\/10.1002\/wics.1443","journal-title":"WIREs Comput. Stat."},{"key":"10192_CR5","doi-asserted-by":"publisher","DOI":"10.1080\/17457300.2020.1818788","author":"B Batomen","year":"2020","unstructured":"Batomen, B., Irving, H., Carabali, M., Carvalho, M.S., Ruggiero, E.D., Brown, P.: Vulnerable road-user deaths in Brazil: a Bayesian hierarchical model for spatial-temporal analysis. Int. J. Injury Cont. Safety Promot. (2020). https:\/\/doi.org\/10.1080\/17457300.2020.1818788","journal-title":"Int. J. Injury Cont. Safety Promot."},{"key":"10192_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5555\/3122009.3242010","volume":"18","author":"AG Baydin","year":"2018","unstructured":"Baydin, A.G., Pearlmutter, B.A., Radul, A.A., Siskind, J.M.: Automatic differentiation in machine learning: a survey. J. Mach. Learn. Res. 18, 1\u201343 (2018). https:\/\/doi.org\/10.5555\/3122009.3242010","journal-title":"J. Mach. Learn. Res."},{"issue":"7572","key":"10192_CR7","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1038\/nature15535","volume":"526","author":"S Bhatt","year":"2015","unstructured":"Bhatt, S., Weiss, D., Cameron, E., Bisanzio, D., Mappin, B., Dalrymple, U., Battle, K., Moyes, C., Henry, A., Eckhoff, P., et al.: The effect of malaria control on plasmodium falciparum in Africa between 2000 and 2015. Nature 526(7572), 207\u2013211 (2015). https:\/\/doi.org\/10.1038\/nature15535","journal-title":"Nature"},{"key":"10192_CR8","doi-asserted-by":"publisher","unstructured":"Bichot, C.-E., Siarry, P.: Graph partitioning. Wiley, Hobroken (2013). https:\/\/doi.org\/10.1007\/978-3-319-63962-8_312-1","DOI":"10.1007\/978-3-319-63962-8_312-1"},{"key":"10192_CR9","doi-asserted-by":"publisher","unstructured":"Bollh\u00f6fer, M., Schenk, O.,\u00a0Janalik, R.,\u00a0Hamm, S.,\u00a0Gullapalli, K.: State-of-the-art sparse direct solvers. In Parallel algorithms in computational science and engineering, pp. 3\u201333. Springer. (2020) https:\/\/doi.org\/10.1007\/978-3-030-43736-7_1","DOI":"10.1007\/978-3-030-43736-7_1"},{"key":"10192_CR10","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1016\/j.ecolmodel.2019.05.005","volume":"405","author":"M Coll","year":"2019","unstructured":"Coll, M., Pennino, M.G., Steenbeek, J., Sol\u00e9, J., Bellido, J.M.: Predicting marine species distributions: complementarity of food-web and bayesian hierarchical modelling approaches. Ecol. Modell. 405, 86\u2013101 (2019). https:\/\/doi.org\/10.1016\/j.ecolmodel.2019.05.005","journal-title":"Ecol. Modell."},{"key":"10192_CR11","doi-asserted-by":"publisher","unstructured":"Congdon, P.: Applied Bayesian modelling, Volume 595. Wiley, Hobroken (2014). https:\/\/doi.org\/10.1002\/9781118895047","DOI":"10.1002\/9781118895047"},{"key":"10192_CR12","doi-asserted-by":"publisher","DOI":"10.1137\/19780898718881","author":"TA Davis","year":"2006","unstructured":"Davis, T.A.: Direct methods for sparse linear systems. SIAM (2006). https:\/\/doi.org\/10.1137\/19780898718881","journal-title":"SIAM"},{"issue":"1","key":"10192_CR13","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/s12080-018-0387-y","volume":"12","author":"OR de Rivera","year":"2019","unstructured":"de Rivera, O.R., Blangiardo, M., L\u00f3pez-Qu\u00edlez, A., Mart\u00edn-Sanz, I.: Species distribution modelling through Bayesian hierarchical approach. Theoret. Ecol. 12(1), 49\u201359 (2019). https:\/\/doi.org\/10.1007\/s12080-018-0387-y","journal-title":"Theoret. Ecol."},{"key":"10192_CR14","doi-asserted-by":"publisher","unstructured":"Demmel, J.W.: Applied numerical linear algebra. Soci. Ind. Appl. Math. https:\/\/doi.org\/10.1137\/19781611971446 (1997)","DOI":"10.1137\/19781611971446"},{"key":"10192_CR15","doi-asserted-by":"crossref","unstructured":"Diaz, J.M., Pophale, S.,\u00a0Hernandez, O., Bernholdt, D.E.,\u00a0Chandrasekaran, S. (2018) Openmp 4.5 validation and verification suite for device offload. In B.\u00a0R. de\u00a0Supinski, P.\u00a0Valero-Lara, X.\u00a0Martorell, S.\u00a0Mateo\u00a0Bellido, and J.\u00a0Labarta (Eds.), Evolving OpenMP for Evolving Architectures, pp. 82\u201395. Springer, Cham https:\/\/www.openmp.org","DOI":"10.1007\/978-3-319-98521-3_6"},{"issue":"1","key":"10192_CR16","doi-asserted-by":"publisher","first-page":"123","DOI":"10.3934\/fods.2021037","volume":"4","author":"EA Fattah","year":"2022","unstructured":"Fattah, E.A., Niekerk, J.V., Rue, H.: Smart gradient - an adaptive technique for improving gradient estimation. Found. Data Sci. 4(1), 123\u2013136 (2022). https:\/\/doi.org\/10.3934\/fods.2021037","journal-title":"Found. Data Sci."},{"issue":"2","key":"10192_CR17","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1137\/0710032","volume":"10","author":"A George","year":"1973","unstructured":"George, A.: Nested dissection of a regular finite element mesh. SIAM J. Numer. Anal. 10(2), 345\u2013363 (1973). https:\/\/doi.org\/10.1137\/0710032","journal-title":"SIAM J. Numer. Anal."},{"issue":"1","key":"10192_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1137\/1031001","volume":"31","author":"A George","year":"1989","unstructured":"George, A., Liu, J.W.: The evolution of the minimum degree ordering algorithm. SIAM Rev. 31(1), 1\u201319 (1989). https:\/\/doi.org\/10.1137\/1031001","journal-title":"SIAM Rev."},{"issue":"3","key":"10192_CR19","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1137\/1033099","volume":"33","author":"MT Heath","year":"1991","unstructured":"Heath, M.T., Ng, E., Peyton, B.W.: Parallel algorithms for sparse linear systems. SIAM Rev. 33(3), 420\u2013460 (1991). https:\/\/doi.org\/10.1137\/1033099","journal-title":"SIAM Rev."},{"issue":"460","key":"10192_CR20","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1198\/016214502388618753","volume":"97","author":"R Henderson","year":"2002","unstructured":"Henderson, R., Shimakura, S., Gorst, D.: Modeling spatial variation in leukemia survival data. J. Am. Stat. Assoc. 97(460), 965\u2013972 (2002). https:\/\/doi.org\/10.1198\/016214502388618753","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"10192_CR21","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.tree.2019.08.006","volume":"35","author":"NJ Isaac","year":"2020","unstructured":"Isaac, N.J., Jarzyna, M.A., Keil, P., Dambly, L.I., Boersch-Supan, P.H., Browning, E., Freeman, S.N., Golding, N., Guillera-Arroita, G., Henrys, P.A., et al.: Data integration for large-scale models of species distributions. Trend. Ecol. Evolut. 35(1), 56\u201367 (2020). https:\/\/doi.org\/10.1016\/j.tree.2019.08.006","journal-title":"Trend. Ecol. Evolut."},{"issue":"1","key":"10192_CR22","doi-asserted-by":"publisher","first-page":"359","DOI":"10.5555\/305219.305248","volume":"20","author":"G Karypis","year":"1998","unstructured":"Karypis, G., Kumar, V.: A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J. Scient. Comp. 20(1), 359\u2013392 (1998). https:\/\/doi.org\/10.5555\/305219.305248","journal-title":"SIAM J. Scient. Comp."},{"key":"10192_CR23","doi-asserted-by":"publisher","first-page":"106316","DOI":"10.1016\/j.envint.2020.106316","volume":"146","author":"G Konstantinoudis","year":"2021","unstructured":"Konstantinoudis, G., Padellini, T., Bennett, J., Davies, B., Ezzati, M., Blangiardo, M.: Long-term exposure to air-pollution and covid-19 mortality in England: a hierarchical spatial analysis. Environ. Int. 146, 106316 (2021). https:\/\/doi.org\/10.1016\/j.envint.2020.106316","journal-title":"Environ. Int."},{"key":"10192_CR24","doi-asserted-by":"crossref","unstructured":"Kontis, V., Bennett, J.E., Rashid, T., Parks, R.M., Pearson-Stuttard, J., Guillot, M., Asaria, P., Zhou, B., Battaglini, M., Corsetti, G., et al.: Magnitude, demographics and dynamics of the effect of the first wave of the covid-19 pandemic on all-cause mortality in 21 industrialized countries. Nat. Med. 26(12), 1919\u20131928 (2020) https:\/\/www.nature.com\/articles\/s41591-020-1112-0","DOI":"10.1038\/s41591-020-1112-0"},{"key":"10192_CR25","doi-asserted-by":"crossref","unstructured":"Krainski, E.T., G\u00f3mez-Rubio, V.,\u00a0Bakka, H.,\u00a0Lenzi, A.,\u00a0Castro-Camilio, D.,\u00a0Simpson, D.,\u00a0Lindgren, F.,\u00a0Rue, H. (2018, December) Advanced spatial modeling with stochastic partial differential equations using R and INLA. CRC press, Cambridge. Github version www.r-inla.org\/spde-book","DOI":"10.1201\/9780429031892"},{"issue":"1137\/1","key":"10192_CR26","first-page":"9780898717839","volume":"10","author":"RJ LeVeque","year":"2007","unstructured":"LeVeque, R.J.: Finite difference methods for ordinary and partial differential equations: steady-state and time-dependent problems. SIAM 10(1137\/1), 9780898717839 (2007)","journal-title":"SIAM"},{"issue":"22","key":"10192_CR27","doi-asserted-by":"publisher","first-page":"9408","DOI":"10.1016\/j.jcp.2008.06.033","volume":"227","author":"S Li","year":"2008","unstructured":"Li, S., Ahmed, S., Klimeck, G., Darve, E.: Computing entries of the inverse of a sparse matrix using the FIND algorithm. J. Comput. Phys. 227(22), 9408\u20139427 (2008). https:\/\/doi.org\/10.1016\/j.jcp.2008.06.033","journal-title":"J. Comput. Phys."},{"key":"10192_CR28","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1007\/398_2020_58","volume":"256","author":"R Lillini","year":"2021","unstructured":"Lillini, R., Tittarelli, A., Bertoldi, M., Ritchie, D., Katalinic, A., Pritzkuleit, R., Launoy, G., Launay, L., Guillaume, E., \u017dagar, T., et al.: Water and soil pollution: ecological environmental study methodologies useful for public health projects. a literature review. Rev. Environ. Contaminat. Toxicol. 256, 179\u2013214 (2021). https:\/\/doi.org\/10.1007\/398_2020_58","journal-title":"Rev. Environ. Contaminat. Toxicol."},{"issue":"8","key":"10192_CR29","doi-asserted-by":"publisher","first-page":"e03721","DOI":"10.1002\/ecs2.3721","volume":"12","author":"D Lindenmayer","year":"2021","unstructured":"Lindenmayer, D., Taylor, C., Blanchard, W.: Empirical analyses of the factors influencing fire severity in southeastern australia. Ecosphere 12(8), e03721 (2021). https:\/\/doi.org\/10.1002\/ecs2.3721","journal-title":"Ecosphere"},{"key":"10192_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.spasta.2022.100599","author":"F Lindgren","year":"2022","unstructured":"Lindgren, F., Bolin, D., Rue, H.: The SPDE approach for gaussian and non-gaussian fields: 10 years and still running. Spat. Stat. (2022). https:\/\/doi.org\/10.1016\/j.spasta.2022.100599","journal-title":"Spat. Stat."},{"issue":"4","key":"10192_CR31","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1111\/j.1467-9868.2011.00777.x","volume":"73","author":"F Lindgren","year":"2011","unstructured":"Lindgren, F., Rue, H., Lindstr\u00f6m, J.: An explicit link between gaussian fields and gaussian markov random fields: the stochastic partial differential equation approach. J. Royal Stat. Soc.: Series B (Stat. Methodol.) 73(4), 423\u2013498 (2011). https:\/\/doi.org\/10.1111\/j.1467-9868.2011.00777.x","journal-title":"J. Royal Stat. Soc.: Series B (Stat. Methodol.)"},{"key":"10192_CR32","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.rse.2018.04.006","volume":"211","author":"N Lu","year":"2018","unstructured":"Lu, N., Liang, S., Huang, G., Qin, J., Yao, L., Wang, D., Yang, K.: Hierarchical Bayesian space-time estimation of monthly maximum and minimum surface air temperature. Remote Sens. Environ. 211, 48\u201358 (2018). https:\/\/doi.org\/10.1016\/j.rse.2018.04.006","journal-title":"Remote Sens. Environ."},{"issue":"11","key":"10192_CR33","doi-asserted-by":"publisher","first-page":"3227","DOI":"10.1007\/s00477-018-1548-7","volume":"32","author":"J Mart\u00ednez-Minaya","year":"2018","unstructured":"Mart\u00ednez-Minaya, J., Cameletti, M., Conesa, D., Pennino, M.G.: Species distribution modeling: a statistical review with focus in spatio-temporal issues. Stoch. Environ. Res. Risk Assess. 32(11), 3227\u20133244 (2018). https:\/\/doi.org\/10.1007\/s00477-018-1548-7","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"10192_CR34","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.csda.2013.04.014","volume":"67","author":"TG Martins","year":"2013","unstructured":"Martins, T.G., Simpson, D., Lindgren, F., Rue, H.: Bayesian computing with inla: new features. Comput. Stat. & Data Anal. 67, 68\u201383 (2013). https:\/\/doi.org\/10.1016\/j.csda.2013.04.014","journal-title":"Comput. Stat. & Data Anal."},{"issue":"530","key":"10192_CR35","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1080\/01621459.2019.1611582","volume":"115","author":"AF Mejia","year":"2020","unstructured":"Mejia, A.F., Yue, Y., Bolin, D., Lindgren, F., Lindquist, M.A.: A bayesian general linear modeling approach to cortical surface FMRI data analysis. J. Am. Stat. Assoc. 115(530), 501\u2013520 (2020). https:\/\/doi.org\/10.1080\/01621459.2019.1611582","journal-title":"J. Am. Stat. Assoc."},{"issue":"12","key":"10192_CR36","doi-asserted-by":"publisher","first-page":"1741","DOI":"10.1111\/ecog.05134","volume":"43","author":"KP Mielke","year":"2020","unstructured":"Mielke, K.P., Claassen, T., Busana, M., Heskes, T., Huijbregts, M.A., Koffijberg, K., Schipper, A.M.: Disentangling drivers of spatial autocorrelation in species distribution models. Ecography 43(12), 1741\u20131751 (2020). https:\/\/doi.org\/10.1111\/ecog.05134","journal-title":"Ecography"},{"key":"10192_CR37","doi-asserted-by":"publisher","unstructured":"Nocedal, J., Wright, S.: Numerical optimization. Springer, Berlin (2006). https:\/\/doi.org\/10.1007\/978-0-387-40065-5","DOI":"10.1007\/978-0-387-40065-5"},{"key":"10192_CR38","unstructured":"Opitz, T. (2017). Latent gaussian modeling and inla: A review with focus on space-time applications. J. de la soci\u00e9t\u00e9 fran\u00e7aise de statistique 158(3), 62\u201385. https:\/\/hal.archives-ouvertes.fr\/hal-01394974"},{"key":"10192_CR39","doi-asserted-by":"publisher","unstructured":"Pan, V.,\u00a0Reif, J. (1985) Efficient parallel solution of linear systems. In Proceedings of the seventeenth annual ACM symposium on Theory of computing, pp. 143\u2013152. https:\/\/doi.org\/10.1145\/22145.22161","DOI":"10.1145\/22145.22161"},{"key":"10192_CR40","unstructured":"PARDISO (2022). Version 7.2. Lugano, Switzerland: Panua Technologies. http:\/\/www.panua.ch"},{"key":"10192_CR41","doi-asserted-by":"publisher","unstructured":"Pimont, F., Fargeon, H., Opitz, T., Ruffault, J., Barbero, R., Martin-StPaul, N., Rigolot, E., Rivi\u00e8re, M., Dupuy, J.-L.: Prediction of regional wildfire activity in the probabilistic bayesian framework of firelihood. Ecol. Appl. 31(5), e02316 (2021). https:\/\/doi.org\/10.1002\/eap.2316","DOI":"10.1002\/eap.2316"},{"key":"10192_CR42","doi-asserted-by":"publisher","first-page":"108084","DOI":"10.1016\/j.agrformet.2020.108084","volume":"291","author":"G Pinto","year":"2020","unstructured":"Pinto, G., Rousseu, F., Niklasson, M., Drobyshev, I.: Effects of human-related and biotic landscape features on the occurrence and size of modern forest fires in Sweden. Agricult. Forest Meteorol. 291, 108084 (2020). https:\/\/doi.org\/10.1016\/j.agrformet.2020.108084","journal-title":"Agricult. Forest Meteorol."},{"key":"10192_CR43","doi-asserted-by":"publisher","unstructured":"Rousseeuw, P.J., Leroy, A.M.: Robust regression and outlier detection, Volume 589. Wiley, Hobroken (2005). https:\/\/doi.org\/10.1002\/0471725382","DOI":"10.1002\/0471725382"},{"key":"10192_CR44","doi-asserted-by":"publisher","unstructured":"Rue, H., Held, L.: Gaussian Markov random fields: theory and applications. CRC Press, Cambridge (2005). https:\/\/doi.org\/10.1201\/9780203492024","DOI":"10.1201\/9780203492024"},{"issue":"10","key":"10192_CR45","doi-asserted-by":"publisher","first-page":"3177","DOI":"10.1016\/j.jspi.2006.07.016","volume":"137","author":"H Rue","year":"2007","unstructured":"Rue, H., Martino, S.: Approximate bayesian inference for hierarchical gaussian markov random field models. J. Stat. Plann. Infer. 137(10), 3177\u20133192 (2007). https:\/\/doi.org\/10.1016\/j.jspi.2006.07.016","journal-title":"J. Stat. Plann. Infer."},{"issue":"2","key":"10192_CR46","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1111\/j.1467-9868.2008.00700.x","volume":"71","author":"H Rue","year":"2009","unstructured":"Rue, H., Martino, S., Chopin, N.: Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. J. Royal Stat. Soc.: Series b (Stat. Methodol.) 71(2), 319\u2013392 (2009). https:\/\/doi.org\/10.1111\/j.1467-9868.2008.00700.x","journal-title":"J. Royal Stat. Soc.: Series b (Stat. Methodol.)"},{"key":"10192_CR47","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1146\/annurev-statistics-060116-054045","volume":"4","author":"H Rue","year":"2017","unstructured":"Rue, H., Riebler, A., S\u00f8rbye, S.H., Illian, J.B., Simpson, D.P., Lindgren, F.K.: Bayesian computing with INLA: a review. Ann. Rev. Stat. Appl. 4, 395\u2013421 (2017). https:\/\/doi.org\/10.1146\/annurev-statistics-060116-054045","journal-title":"Ann. Rev. Stat. Appl."},{"key":"10192_CR48","unstructured":"Rustand, D., Van Niekerk, J., Krainski, E.T.,\u00a0Rue, H.,\u00a0Proust-Lima, C. (2022) Fast and flexible inference approach for joint models of multivariate longitudinal and survival data using integrated nested Laplace approximations. arxiv:2203.06256"},{"issue":"1137\/1","key":"10192_CR49","first-page":"9780898718003","volume":"10","author":"Y Saad","year":"2003","unstructured":"Saad, Y.: Iterative methods for sparse linear systems. SIAM 10(1137\/1), 9780898718003 (2003)","journal-title":"SIAM"},{"issue":"11","key":"10192_CR50","doi-asserted-by":"publisher","first-page":"2487","DOI":"10.3390\/ijerph15112487","volume":"15","author":"S Sanyal","year":"2018","unstructured":"Sanyal, S., Rochereau, T., Maesano, C.N., Com-Ruelle, L., Annesi-Maesano, I.: Long-term effect of outdoor air pollution on mortality and morbidity: a 12-year follow-up study for metropolitan france. Int. J. Environ. Res. Public Health. 15(11), 2487 (2018). https:\/\/doi.org\/10.3390\/ijerph15112487","journal-title":"Int. J. Environ. Res. Public Health."},{"issue":"16","key":"10192_CR51","doi-asserted-by":"publisher","first-page":"9069","DOI":"10.1021\/acs.est.8b02864","volume":"52","author":"G Shaddick","year":"2018","unstructured":"Shaddick, G., Thomas, M.L., Amini, H., Broday, D., Cohen, A., Frostad, J., Green, A., Gumy, S., Liu, Y., Martin, R.V., et al.: Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ. Sci Technol. 52(16), 9069\u20139078 (2018). https:\/\/doi.org\/10.1021\/acs.est.8b02864","journal-title":"Environ. Sci Technol."},{"key":"10192_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.118908","author":"D Spencer","year":"2022","unstructured":"Spencer, D., Yue, Y.R., Bolin, D., Ryan, S., Mejia, A.F.: Spatial bayesian GLM on the cortical surface produces reliable task activations in individuals and groups. NeuroImage (2022). https:\/\/doi.org\/10.1016\/j.neuroimage.2022.118908","journal-title":"NeuroImage"},{"key":"10192_CR53","unstructured":"Takahashi, K.: Formation of sparse bus impedance matrix and its application to short circuit study. In Proc. PICA Conference, June, (1973)"},{"key":"10192_CR54","unstructured":"Toledo, S. (2003). Taucs: a library of sparse linear solvers. https:\/\/www.tau.ac.il\/~stoledo\/taucs\/"},{"key":"10192_CR55","unstructured":"Van\u00a0Merri\u00ebnboer, B., Breuleux, O.,\u00a0Bergeron, A.,\u00a0Lamblin, P. (2018) Automatic differentiation in ML: Where we are and where we should be going. Advances in neural information processing systems 31. https:\/\/proceedings.neurips.cc\/paper\/2018\/file\/770f8e448d07586afbf77bb59f698587-Paper.pdf"},{"key":"10192_CR56","doi-asserted-by":"publisher","unstructured":"Van Niekerk, J., Bakka, H., Rue, H., Schenk, O.: New frontiers in Bayesian modeling using the INLA package in R. J. Stat. Softw. 100(2), 1\u201328 (2021). https:\/\/doi.org\/10.18637\/jss.v100.i02","DOI":"10.18637\/jss.v100.i02"},{"key":"10192_CR57","doi-asserted-by":"publisher","unstructured":"Van Niekerk, J., Bakka, H., Rue, H., Schenk, O.: New frontiers in Bayesian modeling using the INLA package in R. J. Stat. Softw. 100(2), 1\u201328 (2021).https:\/\/doi.org\/10.18637\/jss.v100.i02","DOI":"10.18637\/jss.v100.i02"},{"key":"10192_CR58","doi-asserted-by":"crossref","unstructured":"Van Niekerk, J., E. Krainski, D. Rustand, and H. Rue (2022). A new avenue for bayesian inference with INLA. arXiv preprint arXiv:2204.06797","DOI":"10.1016\/j.csda.2023.107692"},{"key":"10192_CR59","doi-asserted-by":"publisher","unstructured":"Yannakakis, M.: Computing the minimum fill-in is np-complete. SIAM J. Algebr. Discr. Meth. 2(1), 77\u201379 (1981). https:\/\/doi.org\/10.1137\/0602010","DOI":"10.1137\/0602010"}],"container-title":["Statistics and Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11222-022-10192-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11222-022-10192-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11222-022-10192-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,13]],"date-time":"2023-02-13T22:51:18Z","timestamp":1676328678000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11222-022-10192-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,24]]},"references-count":59,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["10192"],"URL":"https:\/\/doi.org\/10.1007\/s11222-022-10192-1","relation":{},"ISSN":["0960-3174","1573-1375"],"issn-type":[{"value":"0960-3174","type":"print"},{"value":"1573-1375","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,24]]},"assertion":[{"value":"15 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 December 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 December 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"25"}}