mgc.sims.ubern {mgc}

Uncorrelated Bernoulli Simulation

Description

A function for Generating an uncorrelated bernoulli simulation.

Usage

mgc.sims.ubern(n, d, eps = 0.5, p = 0.5)

Arguments

n

the number of samples for the simulation.

d

the number of dimensions for the simulation setting.

eps

the noise level for the simulation. Defaults to 0.5.

p

the bernoulli probability.

Value

a list containing the following:

X

[n, d] the data matrix with n samples in d dimensions.

Y

[n] the response array.

Details

Given: w_i = \frac{1}{i} is a weight-vector that scales with the dimensionality. Simumlates n points from Wshape(X, Y) \in \mathbf{R}^d \times \mathbf{R} where:

U \sim Bern(p)

X \sim Bern\left(p\right)^d + \epsilon N(0, I_d)

Y = (2U - 1)w^TX + \epsilon N(0, 1)

For more details see the help vignette: vignette("sims", package = "mgc")

Author(s)

Eric Bridgeford

Examples

library(mgc)
result  <- mgc.sims.ubern(n=100, d=10)  # simulate 100 samples in 10 dimensions
X <- result$X; Y <- result$Y