A simple two-state Markov chain A Markov chain, named after Andrey Markov, is a mathematical system that undergoes transitions from one state to another, between a finite or countable number of possible states. It is a random process characterized as memoryless: the next state depends only on the current state and not on the sequence of events that preceded it. This specific kind of "memoryless...

This paper shows that plausible modifications to the Taylor rule for monetary policy can help explain several empirical anomalies to the behavior of inflation in the new-Keynesian general equilibrium model. The key anomalies considered are (1) the persistence of inflation, both in reduced form and after conditioning on inflation’s driving processes, (2) the positive correlation between the outp...

remote sensing is a key technology for assessing expansion and rate of land cover changes that awareness of these changes as the basic information has a special importance for various programs. in this study, land use changes were examined over the past 24 years, and the feasibility of predicting it in the future was evaluated by using the markov chain model of the abbas plain. landsat tm, etm+...

MOTIVATION Many computational methods for identifying regulatory elements use a likelihood ratio between motif and background models. Often, the methods use a background model of independent bases. At least two different Markov background models have been proposed with the aim of increasing the accuracy of predicting regulatory elements. Both Markov background models suffer theoretical drawback...

Ž The predictability of Lagrangian particle trajectories in the Adriatic Sea a semi-enclosed sub-basin of the Mediterranean . Sea over a period of 1–2 weeks is investigated using three clusters consisting of 5–7 drifters. The analysis is conducted using a Gauss–Markov Lagrangian particle model, which relies on the estimate of climatological mean flow field, persistence of turbulence, and assimi...

This paper analyzes the application of the Markov-switching ARCH model (Hamilton and Susmel, 1994) in improving value-at-risk (VaR) forecast. By considering a mixture of normal distributions with varying variances over different time and regimes, we find that the “spurious high persistence” found in the GARCH model is adjusted. Under relative performance and hypothesis-testing evaluations, the ...

In this paper, we combined the previous model in [ 2 ] with Gray et al.'s work 2012 8 to add telegraph noise by using Markovian switching generate a stochastic SIS epidemic regime switching. Similarly, threshold value for extinction and persistence are then given proved, followed explanation on stationary distribution, where \begin{document}$ M $\end{document} -matrix theory elaborated 20 is fu...

In this paper, we construct a simple model of simultaneous change and persistence in institutions. The model consists of landowning elites and workers, and the key economic decision concerns the form of economic institutions regulating the transaction of labor (e.g., competitive markets versus labor repression). The main idea is that equilibrium economic institutions are a result of the exercis...

We address the batch arrival  systems with finite capacity under partial batch acceptance strategy where service times or rates oscillate between two forms according to the evolution of the number of customers in the system. Applying the theory of Markov regenerative processes and resorting to Markov chain embedding, we present a new algorithm for computing limit distributions of the number cus...

in the present work‎, ‎a new stochastic algorithm is proposed to solve multiple dimensional fredholm integral equations of the second kind‎. ‎the solution of the‎ integral equation is described by the neumann series expansion‎. ‎each term of this expansion can be considered as an expectation which is approximated by a continuous markov chain monte carlo method‎. ‎an algorithm is proposed to sim...