Learn R Programming

TensorComplete

Efficient algorithm 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 algorithm employs the alternating optimization.

Copy Link

Version

Install

install.packages('TensorComplete')

Monthly Downloads

77

Version

0.2.0

License

GPL (>= 2)

Maintainer

Chanwoo Lee

Last Published

April 14th, 2023

Functions in TensorComplete (0.2.0)

fit_continuous_tucker

Signal tensor estimation from a noisy and incomplete data tensor based on the Tucker model.
Altopt

Alternating optimization of the weighted classification loss
likelihood

Log-likelihood function (cost function).
realization

An ordinal-valued tensor randomly simulated from the cumulative model.
fit_nonparaT

Main function for nonparametric tensor estimation and completion based on low sign rank model.
fit_ordinal

Main function for parametric tensor estimation and completion based on ordinal observations.
predict_ordinal

Predict ordinal-valued tensor entries from the cumulative logistic model.
fit_continuous_cp

Signal tensor estimation from a noisy and incomplete data tensor based on CP low rank tensor method.
bic

Bayesian Information Criterion (BIC) value.