RT Journal Article
T1 Change-point detection in multinomial data using phi-divergence test statistics
A1 Batsidis, Apostolos
A1 Horvath, L.
A1 Martín, N.
A1 Pardo Llorente, Leandro
A1 Zografos, Konstantinos
AB We propose two families of maximally selected phi-divergence tests to detect a change in the probability vectors of a sequence of multinomial random variables with possibly different sizes. In addition, the proposed statistics can be used to estimate the location of the change-point. We derive the limit distributions of the proposed statistics under the no change null hypothesis. One of the families has an extreme value limit. The limit of the other family is the maximum of the norm of a multivariate Brownian bridge. We check the accuracy of these limit distributions in case of finite sample sizes. A Monte Carlo analysis shows the possibility of improving the behavior of the test statistics based on the likelihood ratio and chi-square tests introduced in Horvath and Serbinowska [7]. The classical Lindisfarne Scribes problem is used to demonstrate the applicability of the proposed statistics to real life data sets.
PB Academic Press
SN 0047-259X
YR 2013
FD 2013-07
LK https://hdl.handle.net/20.500.14352/33335
UL https://hdl.handle.net/20.500.14352/33335
LA eng
NO NSF
DS Docta Complutense
RD 1 may 2024