Package: mbr 0.0.1.1

Hung Nguyen

mbr: Mass Balance Reconstruction

Mass-balance-adjusted Regression algorithm for streamflow reconstruction at sub-annual resolution (e.g., seasonal or monthly). The algorithm implements a penalty term to minimize the differences between the total sub-annual flows and the annual flow. The method is described in Nguyen et al (2020) <doi:10.1002/essoar.10504791.1>.

Authors:Hung Nguyen

mbr_0.0.1.1.tar.gz
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mbr_0.0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mbr/json (API)

# Install 'mbr' in R:

install.packages('mbr', repos = c('https://critical-infrastructure-systems-lab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ntthung/mbr/issues

Datasets:

p1Seasonal - Seasonal streamflow at P.1 station
pc3seasons - Principal components of tree rings

On CRAN:

3.78 score 1 stars 12 scripts 282 downloads 8 exports 35 dependencies

Last updated from:e5850b4229. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel	NOTE	175
source / vignettes	OK	184
linux-release	NOTE	152
macos-release	NOTE	135
macos-oldrel	NOTE	100
windows-devel	NOTE	110
windows-release	NOTE	116
windows-oldrel	NOTE	95
wasm-release	OK	98

Exports:calculate_metrics cv_mb KGE make_Z mb_reconstruction nRMSE NSE RE

Dependencies:boot cli data.table digest dplR glue lattice lifecycle lme4 magrittr MASS Matrix matrixStats minqa nlme nloptr png R.methodsS3 R.oo R.utils rbibutils Rcpp RcppArmadillo RcppEigen RcppParallel Rdpack reformulas Rfast rlang signal stringi stringr vctrs XML zigg

Streamflow reconstruction with mass balance adjustment

Introduction | Reconstruction | Cross-validation | References

Rendered fromMass-balance-adjusted-regression.Rmdusingknitr::rmarkdown

Last update: 2021-02-10
Started: 2021-02-10

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Back-transformation	back_trans
Reconstruction metrics	calculate_metrics
Scale columns of a matrix	colScale
Unscale columns of a matrix	colUnscale
Cross-validation	cv_mb
Kling-Gupta Efficiency	KGE
Least square with mass balance penalty	lsq_mb
Make cross-validation folds.	make_Z
Fit parameters with mass balance criterion	mb_fit
Mass-balance-adjusted reconstruction	mb_reconstruction
Normalized root-mean-square error	nRMSE
Nash-Sutcliffe Efficiency	NSE
Objective function from parameters	obj_fun
Seasonal streamflow at P.1 station	p1Seasonal
Principal components of tree rings	pc3seasons
Prepend a column of ones	prepend_ones
Reduction of Error	RE
Scale rows of a Matrix	rowScale
Unscale rows of a matrix	rowUnscale