Recursive time series methods are very popular due to their numerical simplicity. Their theoretical background is usually based on Kalman filtering in state space models (mostly in dynamic linear systems). However, in time series practice one must face frequently to outlying values (outliers), which require applying special methods of robust statistics. In the paper a simple robustification of ...

In this paper a general method of constructing control charts for preliminary analysis of individual observations is presented, which is based on recursive score residuals. A simulation study shows that certain implementations of these charts are highly effective in detecting assignable causes.

A general class of recursive residuals is incorporated in the formulation of suitable (aligned) rank tests for change-points pertaining to some simple linear models. The asymptotic theory of the proposed tests rests on some invariance principles for recursively aligned signed rand statistics, and these are developed. Along with the asymptotic properties of the proposed tests, allied efficiency ...

One kind of the colored noise interference systems is generalized output error model (OEARMA). This paper presents a two-stage recursive least squares algorithm for OEARMA. Aiming at the OEARMA, this paper puts forward a two-stage recursive least squares algorithm. The basic idea of the algorithm is to combinie the auxiliary model identification idea and the decomposition technique to decompose...

We developed and implemented change-point recursive models and compared them with a linear recursive model and a standard mixed model (SMM), in the scope of the relationship between litter size (LS) and number of stillborns (NSB) in pigs. The proposed approach allows us to estimate the point of change in multiple-segment modeling of a nonlinear relationship between phenotypes. We applied the pr...

The minimum description length (MDL) has for some decades been known to be an eecient tool for choosing model structure. We will in this contribution generalize MDL to adaptive algorithms in system and signal identiication. The parameter vector in these problems can either be considered as piecewise constant using seg-mentation and change detection algorithms or as time-varying estimated by rec...

The implementation of each function a battery management system (BMS) depends on sensor data. Efficient fault diagnosis is essential to the durability and safety systems. In this paper, model-based scheme fault-tolerant control strategy for voltage current are proposed with recursive least-square (RLS) unscented Kalman filter (UKF) algorithms. uses an open-circuit residual generator capacity ge...

It is well known that the conventional cumulative sum (CUSUM) test suffers from low power and large detection delay. In order to improve of test, we propose two alternative statistics. The backward CUSUM detector considers recursive residuals in reverse chronological order, whereas stacked sequentially cumulates a triangular array backwardly cumulated residuals. A multivariate invariance princi...

Abstract In this contribution, we introduce a generalized Kalman filter with precision in recursive form when the stochastic model is misspecified. The allows for relaxed dynamic which not all state vector elements are connected time. equipped recursion of actual error-variance matrices so as to provide an easy-to-use tool efficient and rigorous analysis case underlying Different mechanizations...

Numerous government surveys of natural resources use Post-Stratifi cation to improve statistical effi ciency, where strata are defi ned by full-coverage, remotely sensed data and geopolitical boundaries. Recursive Restriction Estimation, which may be considered a special case of the static Kalman fi lter, is an attractive alternative. It decomposes a complex estimation problem into simple compo...