Informatica

We present a new method for solving the change-point detection problem for ARMA systems which are assumed to have a slow and non-decaying drift after the change occurs. The proposed technique is inspired by the stochastic complexity theory, which gives a basis of comparison of different models with different change-point times. Some partial results on the analysis of the estimator are stated. A simulation is included which shows that the approach exhibits surprisingly good detection capabilities.

The present paper considers the problem of general estimation of static model parameters and systematic measurement errors. The general estimation algorithm is based on static model linearization and on the least-squares method. The efficiency of this algorithm is illustrated by means of computer-aided digital simulation. The obtained equations and the algorithm of general estimation of static model parameters and systematic measurement errors can be applied for the solution of different practical problems. Estimatibility conditions must be satisfied in all cases.