README.md

In feji3769/simplesim: Simulate Data for Model Building

SimpleSim

Installation

You can download the latest version of SimpleSim from github using :

devtools::install_github("feji3769/SimpleSim")

Introduction

This library contains functions for simulating data. The goal is to have fast and intuitive functions.

The Interface

All the functions are named 'Sim[Dataset]', so for example to simulate blobs you just use SimBlobs(10).

Types of Data

SimpleSim can generate the following data:

1. Blobs [1].
2. Friedman 1 [2].
3. Friedman 2 [2].
4. Friedman 3 [2].
5. 1D mixture of Gaussians.
6. Polynomial change point model.
7. S curve [3]
8. Swiss Roll [4]

References

[1] I. Guyon, "Design of experiments for the NIPS 2003 variable selection benchmark", 2003.

[2] T. Hastie, R. Tibshirani and J. Friedman, "Elements of Statistical Learning Ed. 2", Springer, 2009.

[3] S. Marsland, "Machine Learning: An Algorithmic Perspective", Chapter 10, 2009. http://seat.massey.ac.nz/personal/s.r.marsland/Code/10/lle.py

[4] http://people.cs.uchicago.edu/~dinoj/manifold/swissroll.html

feji3769/simplesim documentation built on Dec. 12, 2020, 10:16 a.m.