| simulation {SmoothTensor} | R Documentation |
Generate a symmetric tensor observation from the smooth signal tensor, Gaussian noise tensor, and permutation.
Description
Generate a symmetric tensor observation from the smooth signal tensor, Gaussian noise tensor, and permutation. Users can select one of 5 different smooth signal tensors generated from functions specified in Table 4 of the reference given below.
Usage
simulation(d, mode = 1, sigma = 0.5, signal_level=5)
Arguments
d |
Dimension of a tensor to be generated. |
mode |
An integer from 1 to 5 corresponding to models specified. Default model is 1. |
sigma |
Standard deviation of the Gaussian noise tensor. Default value is 0.5. |
signal_level |
A scale of the magnitude of the signal tensor to be generated. |
Value
The returned object is a list of components.
signal - A true signal tensor generated from a function specified.
observe - A noisy observation generated from the smooth signal tensor, Gaussian noise tensor, and permutation.
permutation - A true permutation.
References
C. Lee and M. Wang. Smooth tensor estimation with unknown permutations. arXiv:2111.04681, 2021.
Examples
d = 20
# Generate 20 by 20 by 20 observed tesnor generated from model 1
sim1 = simulation(d,mode = 1)
observed_tensor = sim1$observe
signal_tensor = sim1$signal
permutation = sim1$permutation