SignT: Signal tensor estimation from a noisy and incomplete data...

In tensorsign: Nonparametric Tensor Completion via Sign Series

Description

Estimate a signal tensor from a noisy and incomplete data tensor using nonparametric tensor method via sign series.

Usage

SignT(Y,truer,H,Lmin,Lmax,option = 1)

Arguments

Y	A given (possibly noisy and incomplete) data tensor.
truer	Sign rank of the signal tensor.
H	Resolution parameter.
Lmin	Minimum value of the signal tensor (or minimum value of the tensor Y).
Lmax	Maximum value of the signal tensor (or maximum value of the tensor Y).
option	A large margin loss to be used. Use logistic loss if option = 1, hinge loss if option = 2. Logistic loss is default.

Value

The returned object is a list of components.

fitted - A series of optimizers that minimize the weighted classification loss at each pi.

est - An estimated signal tensor based on nonparametic tensor method via sign series.

References

Lee, C., & Wang, M. (2021). Beyond the Signs: Nonparametric Tensor Completion via Sign Series. arXiv preprint arXiv:2102.00384.

Examples

library(rTensor)
indices = c(2,3,4)
noise = rand_tensor(indices)@data
Theta = array(runif(prod(indices),min=-3,max = 3),indices)

# The signal plus noise model
Y = Theta + noise

# Estimate Theta from nonparametic completion method via sign series
hatTheta = SignT(Y,truer = 3,H = 3,Lmin = -3,Lmax = 3, option =1)
print(hatTheta$est)

tensorsign documentation built on Feb. 8, 2021, 5:06 p.m.