In this paper a new non-parametric independence test is presented. García and González-López (2014) [1] introduced the LIS test for the hypothesis of independence between two continuous random variables, the test proposed in this work is a generalization of the LIS test. The new test does not require the assumption of continuity for the random variables, it test is applied to two datasets and also compared with the Pearson’s Chi-squared test.
Topics
Educational assessment
REFERENCES
1.
J. E.
García
and V. A.
González-López
, Independence tests for continuous random variables based on the longest increasing subsequence
. Journal of Multivariate Analysis
127
, 126
–146
, 2014
. Doi:2.
A.
Agresti
, Categorical data analysis
(John Wiley & Sons, Inc.
, Hoboken, New Jersey
, 2002
).3.
J. S.
Simonoff
, Smoothing methods in statistics
(Springer Science & Business Media
, New York
, 1996
)4.
D.
Zelterman
, Goodness-of-fit tests for large sparse multinomial distributions
. Journal of the American Statistical Association
82
(398
), 624
–629
, 1987
.
This content is only available via PDF.
© 2016 Author(s).
2016
Author(s)
You do not currently have access to this content.
