Sie können Bookmarks mittels Listen verwalten, loggen Sie sich dafür bitte in Ihr SLUB Benutzerkonto ein.
Medientyp:
E-Artikel
Titel:
Testing for parameter stability in nonlinear autoregressive models
Beteiligte:
Kirch, Claudia;
Kamgaing, Joseph Tadjuidje
Erschienen:
Wiley, 2012
Erschienen in:
Journal of Time Series Analysis, 33 (2012) 3, Seite 365-385
Sprache:
Englisch
DOI:
10.1111/j.1467-9892.2011.00764.x
ISSN:
0143-9782;
1467-9892
Entstehung:
Anmerkungen:
Beschreibung:
In this article we develop testing procedures for the detection of structural changes in nonlinear autoregressive processes. For the detection procedure, we model the regression function by a single layer feedforward neural network. We show that CUSUM‐type tests based on cumulative sums of estimated residuals, that have been intensively studied for linear regression, can be extended to this case. The limit distribution under the null hypothesis is obtained, which is needed to construct asymptotic tests. For a large class of alternatives, it is shown that the tests have asymptotic power one. In this case, we obtain a consistent change‐point estimator which is related to the test statistics. Power and size are further investigated in a small simulation study with a particular emphasis on situations where the model is misspecified, i.e. the data is not generated by a neural network but some other regression function. As illustration, an application on the Nile data set as well as S&P log‐returns is given.