Model-Selection-Based Monitoring Of Structural Change

Model-Selection-Based Monitoring Of Structural Change

Monitoring Structural Change in Variance , withan

In this paper we propose a sequential testing approach for a structural change in the variance of a time series, which amounts to a procedure with a controlled asymptotic size as we repeat the test. Our approach builds on that taken in Chu, Stinchcombe & White (1996) for structural change in the parameters of a linear regression model. We provide simulation evidence to examine the empirical siz...

Multivariate Methods for Monitoring Structural Change

Detection of structural change is a critical empirical activity, but continuous ‘monitoring’ of series, for structural changes in real time, raises well-known econometric issues that have been explored in a single series context. If multiple series co-break then it is possible that simultaneous examination of a set of series helps identify changes with higher probability or more rapidly than wh...

Monitoring structural change in dynamic econometric models

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 stable, we test whether incoming data are consistent with the previously established relationship. Procedure...

Detection of Process Model Change in Pls Based Performance Monitoring

The detection of process changes using a partial least squares (PLS) based monitoring scheme can be achieved through the interrogation of two metrics, Hotelling's 2 T and the Q-statistic. The Q-statistic has been shown to be insensitive to small changes in the process model parameters. In this paper, a modified statistic based on the local approach is proposed to detect changes in the model par...