dataSimu_element_sparse: Simulate multiple data sets with element-wise sparse patterns

In YipengUva/RpESCA: R implementaion of pESCA models with various concave penalties

Description

This function can generate multiple data sets of mixed data types. Details of the simultion process can be found in the paper https://arxiv.org/abs/1902.06241. In this function, only the element-wise sparsity is included into the loading matrix.

Usage

dataSimu_element_sparse(n, ds, R = 3, dataTypes = "GGG",
  noises = rep(1, 3), margProb = 0.1, sparse_ratio = 0.5,
  SNRs = rep(1, 3))

Arguments

n	the number of objects
ds	a vector for the number of variables in each data set
R	the number of simulated PCs
dataTypes	a string indicates the data type of each data set, possible options include 'G': Gaussian, 'B': Bernoulli.
noises	noise levels of simulated data sets
margProb	desired marginal probability for binary data simulation, used to simulate imbalanced binary data.
sparse_ratio	controls the sparse level of element-wise sparsity
SNRs	the SNRs for the simulation of the multiple data sets

Value

Refer the return of thefunction dataSimu_group_sparse.

Examples

## Not run: 
dataSimulation <- dataSimu_element_sparse(n,ds,R,
                                   dataTypes='GGG',
                                   noises=rep(1,3),
                                   margProb=0.1,sparse_ratio=0.5,
                                   SNRs=rep(1,3))

## End(Not run)

YipengUva/RpESCA documentation built on July 2, 2019, 6:41 p.m.