Package: OrdMonReg 1.0.3

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, Kaspar Rufibach, Filippo Santambrogio

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NEWS

# Install 'OrdMonReg' in R:
install.packages('OrdMonReg', repos = c('https://numbersman77.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • mechIng - Mechanical engineering dataset used to illustrate ordered isotonic regression

On CRAN:

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

1.00 score 4 scripts 193 downloads 14 exports 0 dependencies

Last updated 13 years agofrom:0d35fffb88. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-winNOTENov 23 2024
R-4.5-linuxNOTENov 23 2024
R-4.4-winNOTENov 23 2024
R-4.4-macNOTENov 23 2024
R-4.3-winOKNov 23 2024
R-4.3-macOKNov 23 2024

Exports:astar_1BoundedAntiMeanBoundedAntiMeanTwoBoundedIsoMeanBoundedIsoMeanTwoBoundedIsoMeanTwoDykstrabstar_ndispLSfunctionalMAminK1minK2minK3Subgradient

Dependencies: