A non-parametric spatial independence test using symbolic entropy
In the present paper, we construct a new, simple, consistent and powerful test for spatial independence, called the SG test, by using the new concept of symbolic entropy as a measure of spatial dependence. The standard asymptotic distribution of the test is an affine transformation of the symbolic e...
Gespeichert in:
Veröffentlicht in: | Regional science and urban economics 2010-05, Vol.40 (2), p.106-115 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | In the present paper, we construct a new, simple, consistent and powerful test for spatial independence, called the
SG test, by using the new concept of symbolic entropy as a measure of spatial dependence. The standard asymptotic distribution of the test is an affine transformation of the symbolic entropy under the null hypothesis. The test statistic, with the proposed symbolization procedure, and its standard limit distribution have appealing theoretical properties that guarantee the general applicability of the test. An important aspect is that the test does not require specification of the
W matrix and is free of a priori assumptions. We include a Monte Carlo study of our test, in comparison with the well-known Moran's
I, the
SBDS (
de Graaff et al., 2001) and
τ test (Brett and Pinkse, 1997) that are two non-parametric tests, to better appreciate the properties and the behaviour of the new test. Apart from being competitive compared to other tests, results underline the outstanding power of the new test for non-linear dependent spatial processes. |
---|---|
ISSN: | 0166-0462 1879-2308 |
DOI: | 10.1016/j.regsciurbeco.2009.11.003 |