Search results for "Markov"
showing 10 items of 628 documents
Contributed discussion on article by Pratola
2016
The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.
Juggler's exclusion process
2012
Juggler's exclusion process describes a system of particles on the positive integers where particles drift down to zero at unit speed. After a particle hits zero, it jumps into a randomly chosen unoccupied site. We model the system as a set-valued Markov process and show that the process is ergodic if the family of jump height distributions is uniformly integrable. In a special case where the particles jump according to a set-avoiding memoryless distribution, the process reaches its equilibrium in finite nonrandom time, and the equilibrium distribution can be represented as a Gibbs measure conforming to a linear gravitational potential.
Statistics of residence time for Lévy flights in unstable parabolic potentials
2020
We analyze the residence time problem for an arbitrary Markovian process describing nonlinear systems without a steady state. We obtain exact analytical results for the statistical characteristics of the residence time. For diffusion in a fully unstable potential profile in the presence of Lévy noise we get the conditional probability density of the particle position and the average residence time. The noise-enhanced stability phenomenon is observed in the system investigated. Results from numerical simulations are in very good agreement with analytical ones.
European Option Pricing and Hedging with Both Fixed and Proportional Transaction Costs
2003
Abstract In this paper we provide a systematic treatment of the utility based option pricing and hedging approach in markets with both fixed and proportional transaction costs: we extend the framework developed by Davis et al. (SIAM J. Control Optim., 31 (1993) 470) and formulate the option pricing and hedging problem. We propose and implement a numerical procedure for computing option prices and corresponding optimal hedging strategies. We present a careful analysis of the optimal hedging strategy and elaborate on important differences between the exact hedging strategy and the asymptotic hedging strategy of Whalley and Wilmott (RISK 7 (1994) 82). We provide a simulation analysis in order …
Stochastic Control Problems
2003
The general theory of stochastic processes originated in the fundamental works of A. N. Kolmogorov and A. Ya. Khincin at the beginning of the 1930s. Kolmogorov, 1938 gave a systematic and rigorous construction of the theory of stochastic processes without aftereffects or, as it is customary to say nowadays, Markov processes. In a number of works, Khincin created the principles of the theory of so-called stationary processes.
THE ROLE OF UNBOUNDED TIME-SCALES IN GENERATING LONG-RANGE MEMORY IN ADDITIVE MARKOVIAN PROCESSES
2013
Any additive stationary and continuous Markovian process described by a Fokker–Planck equation can also be described in terms of a Schrödinger equation with an appropriate quantum potential. By using such analogy, it has been proved that a power-law correlated stationary Markovian process can stem from a quantum potential that (i) shows an x-2 decay for large x values and (ii) whose eigenvalue spectrum admits a null eigenvalue and a continuum part of positive eigenvalues attached to it. In this paper we show that such two features are both necessary. Specifically, we show that a potential with tails decaying like x-μ with μ < 2 gives rise to a stationary Markovian process which is not p…
An empirical analysis of growth volatility: A Markov chain approach
2005
This paper studies the determinants of growth rate volatility, focusing on the effect of level of GDP, structural change and the size of economy. First we provide a graphical analysis based on nonparametric techniques, then a quantitative analysis which follows the distribution dynamics approach. Growth volatility appears to (i) decrease with per capita GDP, (ii) increase with the share of the agricultural sector on GDP and, (iii) decrease with the size of the economy, measured by a combination of total GDP and trade openness. However, we show that the explanatory power of per capita GDP tends to vanish when we control for the size of the economy. © 2005 Springer-Verlag Berlin Heidelberg.
Stochastic model of memristor based on the length of conductive region
2021
Abstract We propose a stochastic model of a voltage controlled bipolar memristive system, which includes the properties of widely used dynamic SPICE models and takes into account the fluctuations inherent in memristors. The proposed model is described by rather simple equations of Brownian diffusion, does not require significant computational resources for numerical modeling, and allows obtaining the exact analytical solutions in some cases. The noise-induced transient bimodality phenomenon, arising under resistive switching, was revealed and investigated theoretically and experimentally in a memristive system, by finding a quite good qualitatively agreement between theory and experiment. B…
A Dominance Variant Under the Multi-Unidimensional Pairwise-Preference Framework: Model Formulation and Markov Chain Monte Carlo Estimation.
2018
Forced-choice questionnaires have been proposed as a way to control some response biases associated with traditional questionnaire formats (e.g., Likert-type scales). Whereas classical scoring methods have issues of ipsativity, item response theory (IRT) methods have been claimed to accurately account for the latent trait structure of these instruments. In this article, the authors propose the multi-unidimensional pairwise preference two-parameter logistic (MUPP-2PL) model, a variant within Stark, Chernyshenko, and Drasgow’s MUPP framework for items that are assumed to fit a dominance model. They also introduce a Markov Chain Monte Carlo (MCMC) procedure for estimating the model’s paramete…
A probabilistic expert system for predicting the risk of Legionella in evaporative installations
2011
Research highlights? The bacterium Legionella usually lives in water sources such as cooling towers. ? We discuss a probabilistic expert system for predicting the risk of Legionella. ? The expert system has a master-slave architecture. ? The inference engine is implemented through Bayesian reasoning. ? Bayesian networks model and connect relationships for chemical and physical variables. Early detection in water evaporative installations is one of the keys to fighting against the bacterium Legionella, the main cause of Legionnaire's disease. This paper discusses the general structure, elements and operation of a probabilistic expert system capable of predicting the risk of Legionella in rea…