scholarly journals Transportation inequalities for Markov kernels and their applications

2021 ◽  
Vol 26 (none) ◽  
Author(s):  
Fabrice Baudoin ◽  
Nathaniel Eldredge
Keyword(s):  
Markov Kernels

Markov kernels and tribes

2018 ◽  
Vol 460-461 ◽  
pp. 42-50
Author(s):  
Anatolij Dvurečenskij
Keyword(s):  
Markov Kernels

scholarly journals Asymptotics of Markov Kernels and the Tail Chain

2013 ◽  
Author(s):  
Sidney I. Resnick ◽  
David Zeber
Keyword(s):  
Markov Kernels

scholarly journals Quantum tomography, phase-space observables and generalized Markov kernels

2009 ◽  
Vol 42 (46) ◽  
pp. 465303 ◽  
Author(s):  
Juha-Pekka Pellonpää
Keyword(s):  
Phase Space ◽  
Quantum Tomography ◽  
Markov Kernels

Characterisation of possibility measures of fuzzy events using Markov kernels

1992 ◽  
Vol 46 (2) ◽  
pp. 301-303 ◽  
Author(s):  
Radko Mesiar
Keyword(s):  
Markov Kernels

Representations of state space transformations by Markov kernels

1991 ◽  
Vol 30 (11) ◽  
pp. 1409-1430
Author(s):  
Christian Schindler
Keyword(s):  
State Space ◽  
Markov Kernels

scholarly journals Heavy Tailed Approximate Identities and σ-stable Markov Kernels

2017 ◽  
Vol 48 (4) ◽  
pp. 473-493
Author(s):  
Hugo Aimar ◽  
Ivana Gómez ◽  
Federico Morana
Keyword(s):  
Approximate Identities ◽  
Markov Kernels ◽  
Heavy Tailed

scholarly journals Derivatives of Markov Kernels and Their Jordan Decomposition

2008 ◽  
Vol 14 (1) ◽  
Author(s):  
B. Heidergott ◽  
A. Hordijk ◽  
H. Weisshaupt
Keyword(s):  
Jordan Decomposition ◽  
Markov Kernels ◽  
Derivatives Of

scholarly journals Seismic hazard assessment in the Northern Aegean Sea (Greece) through discrete Semi-Markov modeling.

2016 ◽  
Vol 47 (3) ◽  
pp. 1417
Author(s):  
C. E. Pertsinidou ◽  
G. Tsaklidis ◽  
E. Papadimitriou
Keyword(s):  
Markov Chains ◽  
Seismic Hazard ◽  
Seismic Hazard Assessment ◽  
Aegean Sea ◽  
Arbitrary Distribution ◽  
Markov Modeling ◽  
Sojourn Times ◽  
Markov Kernels ◽  
Northern Aegean Sea ◽  
State 1

Semi-Markov  chains  are  used  for  studying  the  evolution  of  seismicity  in  the Northern Aegean Sea (Greece). Their main difference from the Markov chains is that   they  allow the sojourn times (i.e. the time between successive earthquakes), to follow any arbitrary distribution. It is assumed that the time series of earthquakes that  occurred  in  Northern  Aegean  Sea  form  a  discrete  semi-Markov  chain. The probability law of the sojourn times, is considered to be the geometric distribution or   the   discrete  Weibull  distribution. Firstly,  the  data  are  classified  into  two categories that is, state 1: Magnitude 6.5  -7 and state 2 Magnitude>7, and secondly into three categories , that is    state 1: Magnitude 6.5-6.7, state 2: Magnitude 6.8-7.1 and state 3: Magnitude 7.2-7.4 . This methodology is followed in order to obtain more accurate results and find out whether there exists an impact of the different classification on the results. The parameters of the probability laws of the sojourn times are estimated and the semi-Markov kernels are  evaluated for all the above cases  .  The  semi-Markov  kernels  are  compared and  the   conclusions  are  drawn relatively to future seismic hazard in the area under study.

scholarly journals Duality and intertwining for discrete Markov kernels: relations and examples

2011 ◽  
Vol 43 (02) ◽  
pp. 437-460 ◽  
Author(s):  
Thierry Huillet ◽  
Servet Martinez
Keyword(s):  
Markov Chains ◽  
Probabilistic Interpretation ◽  
Moran Model ◽  
Duality Relations ◽  
Markov Kernels

We supply some relations that establish intertwining from duality and give a probabilistic interpretation. This is carried out in the context of discrete Markov chains, fixing up the background of previous relations established for monotone chains and their Siegmund duals. We revisit the duality for birth-and-death chains and the nonneutral Moran model, and we also explore the duality relations in an ultrametric-type dual that extends the Siegmund kernel. Finally, we discuss the sharp dual, following closely the Diaconis-Fill study.

Concentration of Measure for Products of Markov Kernels and Graph Products via Functional Inequalities

2001 ◽  
Vol 10 (1) ◽  
pp. 1-28 ◽  
Author(s):  
C. HOUDRÉ ◽  
P. TETALI
Keyword(s):  
State Space ◽  
Spectral Gap ◽  
Upper Bounds ◽  
The State ◽  
Concentration Of Measure ◽  
Concentration Inequalities ◽  
Functional Inequalities ◽  
Graph Products ◽  
Markov Kernels

We present versions of concentration inequalities for products of Markov kernels and graph products. We also present discussions of a variety of consequences such as sharp upper bounds, in terms of the diameter of the state space, on the spectral gap.

Sign in / Sign up

Export Citation Format

Share Document