* Correspondence: [email protected] Faculty of Science, Jiangsu University, Zhenjiang 212013, China Full list of author information is available at the end of the article Abstract In this paper, we are to establish a class of strong deviation theorems for the random fields relative to mth-order nonhomogeneous Markov chains indexed by an m rooted Cayley tree. As corollaries, we obtain the st...

In a networked control system scenario, the packet dropout is usually modeled by time-invariant (homogeneous) Markov chain (MC) process. However, from practical point of view, probabilities loss can vary in time and/or probability parameter dependency. Therefore, to design fault detection filter (FDF) implemented semi-reliable communication network, it important consider variation network param...

Intensity estimation is a common problem in statistical analysis of spatial point pattern data. This paper proposes nonparametric Bayesian method for estimating the process intensity based on mixture finite (MFM) model. MFM approach leads to consistent and simultaneous estimate surface clustering information (number clusters configurations) subareas surface. An efficient Markov chain Monte Carl...

A Markov channel is a discrete information channel that includes as special cases the finite state channels and finite state codes of information theory. Kieffer and Rahe proved that one-sided and two-sided Markov channels have the following property: If the input source to a Markov channel is asymptotically mean stationary (AMS), then so is the resulting input-output process and hence the ergo...

We study a semiparametric pseudo-likelihood inference for nonhomogeneous Gamma process with random effects for degradation data. The setting for degradation data is one in which n independent subjects, each with a nonhomogeneous Gamma process, are observed at possible different times. The random effects are used to represent heterogeneity of degradation paths. To obtain the maximum pseudo-likel...