SignT: Estimation of a signal tensor from a noisy and incomplete...
In Chanwoost/tensorsign: Nonparametric Tensor Completion Via Sign Series

Description Usage Arguments Value References Examples

View source: R/signT.R

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

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

`Y`	A given data tensor (possibly noisy and incomplete).
`truer`	A sign rank of the signal tensor.
`H`	A resolution parameter.
`Lmin`	A minimum value of the signal tensor (or a minimum value of the tensor Y).
`Lmax`	A maximum value of the signal tensor (or a 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.

The returned value is a list with components.

fitted A series of optimizers that minimize the weighted classification loss at a given level pi.

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

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

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 = 5,Lmin = -3,Lmax = 3, option =1)
print(hatTheta$est)