#
Least-Squares Independence Test (LSIT)

##
Description

*Least-Squares Independence Test (LSIT)*
is a method of testing the null hypothesis that
paired (input-output) samples are independent.
LSIT adopts a squared-loss variant of mutual information as
an independence measure and estimates it using the density-ratio
estimation method uLSIF.
Thanks to this formulation, all tuning parameters
such as the Gaussian width and the regularization parameter
can be automatically chosen based on a cross-validation method.

##
Download

MATLAB implementation of LSIT:
LSIT.tgz
("demo_LSIT.m" is the first file to execute).

##
Examples

##
References

Sugiyama, M. & Suzuki, T.

Least-squares independence test.

*IEICE Transactions on Information and Systems*,
vol.E94-D, no.6, pp.1333-1336, 2011.

[
paper
]

Masashi Sugiyama
(sugi [at] cs.titech.ac.jp)

Sugiyama Laboratory,
Department of Computer Science,
Graduate School of Information Science and Engineering,
Tokyo Institute of Technology,

2-12-1-W8-74, O-okayama, Meguro-ku, Tokyo, 152-8552, Japan.

TEL & FAX: +81-3-5734-2699