Showing 1 - 7 of 7
In many applications one is interested to detect certain (known) patterns in the mean of a process with smallest delay. Using an asymptotic framework which allows to capture that feature, we study a class of appropriate sequential nonparametric kernel procedures under local nonparametric...
Persistent link: https://www.econbiz.de/10010509828
Motivated in part by applications in model selection in statistical genetics and sequential monitoring of financial data, we study an empirical process framework for a class of stopping rules which rely on kernel-weighted averages of past data. We are interested in the asymptotic distribution...
Persistent link: https://www.econbiz.de/10010509838
We derive the limiting null distributions of the standard and OLS based CUSUM-tests for structural change of the coecients of a linear regression model in the context of long memory disturbances. We show that both tests behave fundamentally different in a long memory environment, as compared to...
Persistent link: https://www.econbiz.de/10009783563
The paper presents an approach to the analysis of data that contains (multiple) structural changes in a linear regression setup. We implement various strategies which have been suggested in the literature for testing against structural changes as well as a dynamic programming algorithm for the...
Persistent link: https://www.econbiz.de/10009770910
The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation-type tests in a monitoring situation – given a history period for which a regression relationship is known to be...
Persistent link: https://www.econbiz.de/10009775964
In this paper, we consider three major types of nonparametric regression tests that are based on kernel and local polynomial smoothing techniques. Their asymptotic power comparisons are established systematically under the fixed and contiguous alternatives, and are also illustrated through...
Persistent link: https://www.econbiz.de/10010509837
We consider the finite sample power of various tests against serial correlation in the disturbances of a linear regression when these disturbances follow a stationary long memory process. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin-Watson test...
Persistent link: https://www.econbiz.de/10010516924