gaussian_fun {gsaot} | R Documentation |
Multivariate Gaussian linear model evaluation
Description
Generates samples from a multivariate Gaussian distribution and evaluates a simple linear transformation model.
Usage
gaussian_fun(N)
Arguments
N |
Number of input samples to generate. |
Details
Inputs x
are sampled from:
\mathbf{X} \sim \mathcal{N}(\boldsymbol{\mu}, \Sigma), \quad \boldsymbol{\mu} = [1, 1, 1], \quad \Sigma = \begin{bmatrix} 1 & 0.5 & 0.5 \\ 0.5 & 1 & 0.5 \\ 0.5 & 0.5 & 1 \end{bmatrix}
The output is given by:
\mathbf{Y} = A \mathbf{X}^{\top}, \quad A = \begin{bmatrix} 4 & -2 & 1 \\ 2 & 5 & -1 \end{bmatrix}
Value
A list with two elements:
-
x
: a numeric matrix of sizeN x 8
containing the input samples. -
y
: a numeric vector of lengthN
with the corresponding function outputs.
See Also
Examples
result <- gaussian_fun(1000)
head(result$x)
head(result$y)
[Package gsaot version 1.1.0 Index]