The open source RFortran library for accessing R from Fortran, with applications in environmental modelling

Environmental Modelling and Software

Volumn 26, Issue 2, 2011, Pages 219-234

  Thyer, Mark ^a   Leonard, Michael ^b   Kavetski, Dmitri ^a   Need, Stephen ^b   Renard, Benjamin ^c  

^a UNIVERSITY OF NEWCASTLE   (Australia)

^b UNIVERSITY OF ADELAIDE   (Australia)

^c CENTRE DE LYON VILLEURBANNE   (France)

Author keywords

COM; Fortran; Open Source Software; R

Indexed keywords

COASTAL FLOODING; COM; COMPONENT OBJECT MODELS; DYNAMIC LINK LIBRARY; ENVIRONMENTAL MODELLING; FORTRAN; FORTRAN CODES; FORTRAN PROGRAMS; HYDROLOGICAL MODELS; INTERACTIVE MODELS; JOINT PROBABILITY; METHOD AND SOFTWARE DEVELOPMENT; MICROSOFT WINDOWS; NUMERICAL QUADRATURE; OPEN SOURCE SOFTWARE; OPEN SOURCES; OPERATING SYSTEMS; R; R PROGRAMMING; SCIENTISTS AND ENGINEERS; STATISTICAL PACKAGES; VISUAL FORTRAN; VISUALIZATION PACKAGES; HYDROLOGICAL MODEL CALIBRATIONS;

COMPUTER SOFTWARE; EMBEDDED SYSTEMS; HYDRAULIC MODELS; HYDRAULIC STRUCTURES; MATHEMATICAL PROGRAMMING; OPEN SYSTEMS; PACKAGING; PROBABILITY DENSITY FUNCTION; PROGRAM COMPILERS; PROGRAM INTERPRETERS; SOFTWARE DESIGN; VISUALIZATION; WINDOWS OPERATING SYSTEM;

FORTRAN (PROGRAMMING LANGUAGE);

CALIBRATION; COASTAL ZONE; DATA SET; ENVIRONMENTAL MODELING; FLOODING; HYDROLOGICAL MODELING; MATHEMATICAL ANALYSIS; NUMERICAL MODEL; SOFTWARE; STATISTICAL ANALYSIS; VISUALIZATION;

EID: 78049294593     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2010.05.007     Document Type: Article

References (23)

1. Abramowitz G., Wang Y., Pak B. A User Guide for the ACCESS Land Surface Model 2007, CSIRO Marine and Atmospheric Research.
2. Baier T. rcom: R COM Client Interface and Internal COM Server 2009, http://cran.r-project.org/web/packages/rcom/, R package version 2.1.1.
3. Baier T. R as a Service: statconnWS (accessed 12.06.10). http://learnserver2.csd.univie.ac.at/rcomwiki/doku.php%3Fid%3Dstatconnws.
4. Baier T., Neuwirth E. Excel:: COM:: R. Computational Statistics 2007, 22(1):91-108.
5. Canaimasoft f90VB User Manual 2000, http://www.canaimasoft.com/f90vb/.
6. Cowles M., Carlin B.P. Markov chain Monte Carlo convergence diagnostics: a comparative review. Journal of the American Statistical Association 1996, 91:883-904.
7. Favre A.C., Adlouni S.E., Perreault L., Thiemonge N., Bobee B. Multivariate hydrological frequency analysis using copulas. Water Resources Research 2004, 40(1):W01101.
8. Giunta G., Mariani P., Montella R., Riccio A. pPOM: a nested, scalable, parallel and Fortran 90 implementation of the Princeton Ocean Model. Environmental Modelling and Software 2007, 22(1):117-122.
9. Kavetski D., Kuczera G., Franks S.W. Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory. Water Resources Research 2006, 42(3). 10.1029/2005WR004368.
10. Kojadinovic I., Yan J. Modeling multivariate distributions with continuous margins using the copula R package. Journal of Statistical Software 2010, 34(9):1-20 http://www.jstatsoft.org/v34/i09/.
11. Kuczera G., Renard B., Kavetski D., Thyer M.A. A limited-memory acceleration strategy for MCMC sampling in hierarchical Bayesian calibration of hydrological models. Water Resources Research 2010, 46:W07602. 10.1029/2009WR008985.
12. Lang D.T. RDCOMServer: R-DCOM object server http://www.omegahat.org.
13. Lemmon D.R., Schafer J.L. Developing Statistical Software in Fortran 95 2005, Springer, New York, USA.
14. Maindonald J., Braun J. Data Analysis and Graphics Using R - An Example-Based Approach 2007, Cambridge University Press. second ed.
15. Mathworks, 2007. Matlab: The Language of Scientific Computing.
16. McDonald M.G., Harbaugh A.W. The history of MODFLOW. Groundwater 2003, 41(2):280-283.
17. Need, S., Lambert M, Metcalfe A., 2008. A total probability approach to flood frequency analysis in tidal river reaches. In: Proceedings of the World Environmental and Water Resources Congress, Ahupua'a, Hawaii, ISBN.
18. Object Management Group, I., 2002. Common Object Request Broker Architecture: Core Specification. Specification 3.0, Nov 2002.
19. R Development Core Team R: A Language and Environment for Statistical Computing 2010, R Foundation for Statistical Computing, Vienna, Austria. http://www.r-project.org.
20. Tan K.S., Chiew F.H.S., Grayson B. Stochastic event-based approach to generate concurrent hourly mean sea level pressure and wind sequences for estuarine flood risk assessment. ASCE Journal of Hydrologic Engineering 2008, 13(6):449-460.
21. Thyer M., Renard B., Kavetski D., Kuczera G., Franks S.W., Srikanthan S. Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: a case study using Bayesian total error analysis. Water Resources Research 2009, 45:W00B14. 10.1029/2008WR006825.
22. Tolson B.A., Shoemaker C.A. Efficient prediction uncertainty approximation in the calibration of environmental simulation models. Water Resources Research 2008, 44(11).
23. Vance A. Data analysts captivated by R's power http://www.nytimes.com/2009/01/07/technology/business-computing/07program.html.