Package: OrdMonReg 1.0.4

OrdMonReg: Compute Least Squares Estimates of One Bounded or Two Ordered Isotonic Regression Curves

We consider the problem of estimating two isotonic regression curves g1* and g2* under the constraint that they are ordered, i.e. g1* <= g2*. Given two sets of n data points y_1, ..., y_n and z_1, ..., z_n that are observed at (the same) deterministic design points x_1, ..., x_n, the estimates are obtained by minimizing the Least Squares criterion L(a, b) = sum_{i=1}^n (y_i - a_i)^2 w1(x_i) + sum_{i=1}^n (z_i - b_i)^2 w2(x_i) over the class of pairs of vectors (a, b) such that a and b are isotonic and a_i <= b_i for all i = 1, ..., n. We offer two different approaches to compute the estimates: a projected subgradient algorithm where the projection is calculated using a PAVA as well as Dykstra's cyclical projection algorithm.

Authors:Fadoua Balabdaoui [aut], Kaspar Rufibach [aut, cre], Filippo Santambrogio [aut]

OrdMonReg_1.0.4.tar.gz
OrdMonReg_1.0.4.zip(r-4.7)OrdMonReg_1.0.4.zip(r-4.6)OrdMonReg_1.0.4.zip(r-4.5)
OrdMonReg_1.0.4.tgz(r-4.6-any)OrdMonReg_1.0.4.tgz(r-4.5-any)
OrdMonReg_1.0.4.tar.gz(r-4.7-any)OrdMonReg_1.0.4.tar.gz(r-4.6-any)
OrdMonReg_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
OrdMonReg/json (API)
NEWS

# Install 'OrdMonReg' in R:
install.packages('OrdMonReg', repos = c('https://numbersman77.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • mechIng - Mechanical engineering dataset used to illustrate ordered isotonic regression

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 6 scripts 290 downloads 14 exports 0 dependencies

Last updated from:97bb7fa618. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK95
source / vignettesOK137
linux-release-x86_64OK92
macos-release-arm64OK83
macos-oldrel-arm64OK88
windows-develOK66
windows-releaseOK60
windows-oldrelOK51
wasm-releaseOK113

Exports:astar_1BoundedAntiMeanBoundedAntiMeanTwoBoundedIsoMeanBoundedIsoMeanTwoBoundedIsoMeanTwoDykstrabstar_ndispLSfunctionalMAminK1minK2minK3Subgradient

Dependencies: