Miscellaneous Resources for Traffic Estimation Methods

Introductory materials for INLA and Bayesian methods

Introduction to INLA: https://www.paulamoraga.com/book-geospatial/sec-arealdataexamplespatial.html
Advanced INLA: https://becarioprecario.bitbucket.io/inla-gitbook/
Review of INLA: Rue, H., Riebler, A., Sørbye, S.H., Illian, J.B., Simpson, D.P. and Lindgren, F.K., 2017. Bayesian computing with INLA: a review. Annual Review of Statistics and Its Application, 4, pp.395-421.
INLA https://groups.google.com/g/r-inla-discussion-group/c/wA8nJW22BSo
McElreath, R. 2020. Statistical rethinking : a Bayesian course with examples in R and Stan Second edition. Boca Raton ;: CRC Press, Taylor & Francis Group.
sDNA https://sdna.cardiff.ac.uk/:
- Cooper, C.H.V., Chiaradia, A.J.F., 2020. sDNA: 3-d spatial network analysis for GIS, CAD, Command Line & Python. SoftwareX 12, 100525. https://doi.org/10.1016/j.softx.2020.100525

https://github.com/ITSLeeds/trafficEstimatr
A spatio-temporal approach to review: Boulieri, A., Liverani, S., de Hoogh, K. and Blangiardo, M., 2017. A space–time multivariate Bayesian model to analyse road traffic accidents by severity. Journal of the Royal Statistical Society: Series A (Statistics in Society), 180(1), pp.119-139.