Package: TensorComplete 0.2.0

Chanwoo Lee

TensorComplete: Tensor Noise Reduction and Completion Methods

Efficient algorithms for tensor noise reduction and completion. This package includes a suite of parametric and nonparametric tools for estimating tensor signals from noisy, possibly incomplete observations. The methods allow a broad range of data types, including continuous, binary, and ordinal-valued tensor entries. The algorithms employ the alternating optimization. The detailed algorithm description can be found in the following three references.

Authors:Chanwoo Lee <[email protected]>, Miaoyan Wang <[email protected]>

TensorComplete_0.2.0.tar.gz
TensorComplete_0.2.0.tar.gz(r-4.5-noble)TensorComplete_0.2.0.tar.gz(r-4.4-noble)
TensorComplete_0.2.0.tgz(r-4.4-emscripten)TensorComplete_0.2.0.tgz(r-4.3-emscripten)
TensorComplete.pdf |TensorComplete.html
TensorComplete/json (API)

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

Peer review:

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

1.70 score 188 downloads 9 exports 3 dependencies

Last updated 2 years agofrom:cbfd84298e. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-linuxOKOct 10 2024

Exports:Altoptbicfit_continuous_cpfit_continuous_tuckerfit_nonparaTfit_ordinallikelihoodpredict_ordinalrealization

Dependencies:MASSpracmatensorregress