Titlebook: Stochastic Models, Statistics and Their Applications; Wrocław, Poland, Feb Ansgar Steland,Ewaryst Rafajłowicz,Krzysztof Szajo Conference pr

surrogate

委托

Kernel Estimation of Wiener–Hammerstein System Nonlinearityd by random processes. Two kernel-based methods are presented and compared. The proposed estimates are consistent under small amount of a priori information. An IIR dynamics, non-invertible static non-linearity, and non-Gaussian excitations are admitted. The convergence of the estimates is proved fo

CLIFF

Monitoring Changes in RCA Modelsodel of general order p. A given set of historical stable observations is available that serves as a training sample. The proposed monitoring procedure is based on the quasi-likelihood scores and the quasi-maximum likelihood estimators of the respective parameters computed from the training sample,

Jejune

Detecting Changes in Spatial-Temporal Image Data Based on Quadratic Forms we consider a detector based on linear combinations of quadratic forms, thus allowing to consider linear contrasts of subimages in terms of their average grey value. We derive the asymptotic distribution of the proposed detector and the underlying empirical processes under the no-change null hypoth

针叶类的树

Optimal Designs for Steady-State Kalman Filters consists of an allocation of available resources to these sensors. We formalize the problem of selecting a design that maximizes the information matrix of the steady-state of the Kalman filter, with respect to a standard optimality criterion, such as .- or .-optimality. This problem generalizes the

喷出

pancreas

carotenoids

abysmal

Model Selection Using Cramér–von Mises Distanceic, to decide which class approximates the underlying distribution better. With increasing sample size the asymptotic normality property of our test statistic is shown under suitable conditions. As an example, we apply our method to a real data set of lifetimes of DC-motors, which depend on the covariate ..

简洁