<?php echo $group

From noreply at r-forge.r-project.org Mon May 18 10:45:43 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 18 May 2015 10:45:43 +0200 (CEST) Subject: [Dream-commits] r40 - pkg/R Message-ID: <20150518084543.4071D187645@r-forge.r-project.org> Author: josephguillaume Date: 2015-05-18 10:45:42 +0200 (Mon, 18 May 2015) New Revision: 40 Modified: pkg/R/dream.R pkg/R/handleBounds.R Log: Fix handleBounds rand Modified: pkg/R/dream.R =================================================================== --- pkg/R/dream.R 2012-09-13 01:35:17 UTC (rev 39) +++ pkg/R/dream.R 2015-05-18 08:45:42 UTC (rev 40) @@ -51,7 +51,7 @@ eps = 5e-2, ## Random error for ergodicity outlierTest = 'IQR_test', ## What kind of test to detect outlier chains? pCR.Update = TRUE, ## Adaptive tuning of crossover values - boundHandling = 'reflect', ## Boundary handling: "reflect", "bound", "fold", "none" + boundHandling = 'reflect', ## Boundary handling: "reflect", "bound", "fold", "none","rand" burnin.length=0.1, ## Proportion of iterations considered to be burnin. 0 to turn off. ### Termination criteria. TODO: are the 2nd two valid, given that ndraw is used in adaptive pcr ndraw = 1e5, ## maximum number of function evaluations @@ -200,7 +200,7 @@ ## Check validity of settings if (control$DEpairs==0) stop("control$DEpairs set to 0. Increase nseq?") stopifnot(control$DEpairs<=(control$nseq-1)/2) ## Requirement of offde - stopifnot(control$boundHandling %in% c("reflect", "bound", "fold", "none")) + stopifnot(control$boundHandling %in% c("reflect", "bound", "fold", "none","rand")) if (control$boundHandling == 'none') warning("No bound handling in use, parameters may cause errors elsewhere") stopifnot(control$REPORT>=0) if (control$parallel=="snow.chains"){ Modified: pkg/R/handleBounds.R =================================================================== --- pkg/R/handleBounds.R 2012-09-13 01:35:17 UTC (rev 39) +++ pkg/R/handleBounds.R 2015-05-18 08:45:42 UTC (rev 40) @@ -34,7 +34,7 @@ }, none = x, rand = { - x[c(too.low,too.high),p] <- lower[p] + runif(1)*(upper[p]-lower[p]) + x[c(too.low,too.high),p] <- lower[p] + runif(length(too.low)+length(too.high))*(upper[p]-lower[p]) }, stop("Unrecognised value of 'bound.handling'") )#switch From noreply at r-forge.r-project.org Mon May 18 11:09:20 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Mon, 18 May 2015 11:09:20 +0200 (CEST) Subject: [Dream-commits] r41 - www Message-ID: <20150518090920.C07271808F5@r-forge.r-project.org> Author: josephguillaume Date: 2015-05-18 11:09:20 +0200 (Mon, 18 May 2015) New Revision: 41 Modified: www/index.php Log: Add reference to 2013 swat paper Modified: www/index.php =================================================================== --- www/index.php 2015-05-18 08:45:42 UTC (rev 40) +++ www/index.php 2015-05-18 09:09:20 UTC (rev 41) @@ -1,107 +1,108 @@ - - - - -'; -?> - - - - - - <?php echo $group_name; ?> - - - - - - - - -

- - - - - - - - - -

The project summary page you can find here.

- -For information on how to use dream, please run in R:

help("dreamCalibrate") - to calibrate a function using dream
help("dream") - for low-level interface
demo(example1) - Fitting a banana shaped distribution
demo(example2) - Fitting an n-dimensional Gaussian distribution
demo(FME.nonlinear.model) - Calibrating the non-linear model shown - in the FME package vignette
demo(FME.nonlinear.model_parallelisation) - Example of parallelisation using the SNOW package
demo(parallelisation_chain_id) - Example of parallelisation when DREAM calls an external model using batch files in separate folders.

-To cite the DREAM algorithm please use: -

- Vrugt, J. A., ter Braak, C. J. F., Diks, C. G. H., Robinson, B. A., - Hyman, J. M., Higdon, D., 2009. Accelerating Markov chain Monte Carlo - simulation by differential evolution with self-adaptive randomized - subspace sampling. International Journal of Nonlinear Sciences - and Numerical Simulation 10 (3), 273-290. DOI: 10.1515/IJNSNS.2009.10.3.273 -

-To cite the dream package, please use:

- Joseph Guillaume and Felix Andrews (2012). dream: DiffeRential - Evolution Adaptive Metropolis. R package version 0.4-2. URL - http://CRAN.R-project.org/package=dream -

- -For additional information on the algorithm also see:

- Vrugt, J. A., ter Braak, C. J. F., Gupta, H. V., Robinson, B. A., - 2009. Equifinality of formal (DREAM) and informal (GLUE) Bayesian - approaches in hydrologic modeling? - Stochastic Environmental Research and Risk Assessment 23 (7), 1011--1026. - DOI: 10.1007/s00477-008-0274-y -
-An example of parallelisation of DREAM for the SWAT model (ZIP file) can be downloaded. Thanks to John Joseph for this contribution. -

- -

-This implementation of DREAM has been tested against the original Matlab implementation. See example1.R and example2.R -

-Please note that the dream_zs and dream_d algorithms may be superior in your circumstances. These are not implemented in this package. Please read the following references for details: -

-Vrugt, J. A. and Ter Braak, C. J. F. (2011) DREAM(D): an adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems, Hydrol. Earth Syst. Sci., 15, 3701-3713, DOI: 10.5194/hess-15-3701-2011 -
-ter Braak, C. and J. Vrugt (2008). Differential Evolution Markov Chain -with snooker updater and fewer chains. Statistics and Computing 18(4): 435-446 DOI: 10.1007/s11222-008-9104-9 -
-Laloy,E., and J.A. Vrugt. 2012. High-dimensional posterior exploration -of hydrologic models using multiple-try DREAM(ZS) and high-performance -computing. Water Resources Research, 48, W0156. DOI 10.1029/2011WR010608 -

- - - + + + + +'; +?> + + + + + + <?php echo $group_name; ?> + + + + + + + + +

+ + + + + + + + + +

The project summary page you can find here.

+ +For information on how to use dream, please run in R:

help("dreamCalibrate") - to calibrate a function using dream
help("dream") - for low-level interface
demo(example1) - Fitting a banana shaped distribution
demo(example2) - Fitting an n-dimensional Gaussian distribution
demo(FME.nonlinear.model) - Calibrating the non-linear model shown + in the FME package vignette
demo(FME.nonlinear.model_parallelisation) - Example of parallelisation using the SNOW package
demo(parallelisation_chain_id) - Example of parallelisation when DREAM calls an external model using batch files in separate folders.

+To cite the DREAM algorithm please use: +

+ Vrugt, J. A., ter Braak, C. J. F., Diks, C. G. H., Robinson, B. A., + Hyman, J. M., Higdon, D., 2009. Accelerating Markov chain Monte Carlo + simulation by differential evolution with self-adaptive randomized + subspace sampling. International Journal of Nonlinear Sciences + and Numerical Simulation 10 (3), 273-290. DOI: 10.1515/IJNSNS.2009.10.3.273 +

+To cite the dream package, please use:

+ Joseph Guillaume and Felix Andrews (2012). dream: DiffeRential + Evolution Adaptive Metropolis. R package version 0.4-2. URL + http://CRAN.R-project.org/package=dream +

+ +For additional information on the algorithm also see:

+ Vrugt, J. A., ter Braak, C. J. F., Gupta, H. V., Robinson, B. A., + 2009. Equifinality of formal (DREAM) and informal (GLUE) Bayesian + approaches in hydrologic modeling? + Stochastic Environmental Research and Risk Assessment 23 (7), 1011--1026. + DOI: 10.1007/s00477-008-0274-y +
+An example of parallelisation of DREAM for the SWAT model (ZIP file) can be downloaded. Thanks to John Joseph for this contribution. This example is documented in the publication: +
Joseph, J.F., J.H.A. Guillaume (2013) Using a parallelized MCMC algorithm in R to identify appropriate likelihood functions for SWAT, Environmental Modelling & Software, 46, pp 292-298, DOI: 10.1016/j.envsoft.2013.03.012. +

+ +

+This implementation of DREAM has been tested against the original Matlab implementation. See example1.R and example2.R +

+Please note that the dream_zs and dream_d algorithms may be superior in your circumstances. These are not implemented in this package. Please read the following references for details: +

+Vrugt, J. A. and Ter Braak, C. J. F. (2011) DREAM(D): an adaptive Markov Chain Monte Carlo simulation algorithm to solve discrete, noncontinuous, and combinatorial posterior parameter estimation problems, Hydrol. Earth Syst. Sci., 15, 3701-3713, DOI: 10.5194/hess-15-3701-2011 +
+ter Braak, C. and J. Vrugt (2008). Differential Evolution Markov Chain +with snooker updater and fewer chains. Statistics and Computing 18(4): 435-446 DOI: 10.1007/s11222-008-9104-9 +
+Laloy,E., and J.A. Vrugt. 2012. High-dimensional posterior exploration +of hydrologic models using multiple-try DREAM(ZS) and high-performance +computing. Water Resources Research, 48, W0156. DOI 10.1029/2011WR010608 +

+ + +