R: Wrapper function to generate data from a variety of...

sim_data {clusteval} | R Documentation

## Wrapper function to generate data from a variety of data-generating models.

### Description

We provide a wrapper function to generate from three data-generating models:

`sim_unif`

  Five multivariate uniform distributions

`sim_normal`

  Multivariate normal distributions with intraclass covariance matrices

`sim_student`

  Multivariate Student's t distributions each with a common covariance matrix

### Usage

      sim_data(family = c("uniform", "normal", "student"), ...)

### Arguments

`family` | the family of distributions from which to generate data
`...` | optional arguments that are passed to the data-generating function

### Details

For each data-generating model, we generate n_m observations (m = 1, …, M) from each of M multivariate distributions so that the Euclidean distance between each of the population centroids and the origin is equal and scaled by Δ ≥ 0. For each model, the argument `delta` controls this separation.

This wrapper function is useful for simulation studies, where the efficacy of supervised and unsupervised learning methods and algorithms are evaluated as a the population separation is increased.

### Value

named list containing:

x:

  A matrix whose rows are the observations generated and whose columns are the `p` features (variables)

y:

  A vector denoting the population from which the observation in each row was generated.

### Examples

    set.seed(42)
    uniform_data <- sim_data(family = "uniform")
    normal_data <- sim_data(family = "normal", delta = 2)
    student_data <- sim_data(family = "student", delta = 1, df = 1:5)

[Package clusteval version 0.1 Index]