Results 61 to 70 of about 1,619 (185)
Filtering and change point estimation for hidden Markov-modulated Poisson processes
Applied Mathematics Letters, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robert J. Elliott, Tak Kuen Siu
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Choice of the Parameters of the CUSUM Algorithms for Parameter Estimation in the Markov Modulated Poisson Process [PDF]
Proceedings of the 2016 Conference on Information Technologies in Science, Management, Social Sphere and Medicine, 2016 CUSUM algorithm for controlling chain state switching in the Markov modulated Poisson process was investigated via simulation. Recommendations concerning the parameter choice were given subject to characteristics of the process. Procedure of the process parameter estimation was described.
Burkatovskaya, Yuliya Borisovna +2 more
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Variable Selection for Illness‐Death Processes Under Dual Observation Schemes
Statistics in Medicine, Volume 45, Issue 13-14, June 2026.ABSTRACT The classical illness‐death process offers a useful framework for studying the progression of chronic disease while jointly modeling death. In many settings the time of disease progression is not observed directly, but progression status is recorded at intermittent assessment times.
Xianwei Li, Liqun Diao, Richard J. Cook
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eDNA signals improve local predictions of fish abundances in Mediterranean coastal ecosystems
Journal of Applied Ecology, Volume 63, Issue 6, June 2026.This study demonstrates that integrating eDNA metabarcoding data into species distribution models can improve fish abundance predictions, especially for site‐attached and reef‐associated species. This approach provides a scalable and cost‐effective tool for monitoring, impact assessment, spatial planning and adaptive management of marine resources ...
Noémie Coulon +14 more
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Non-identifiability of the two state Markovian Arrival process [PDF]
In this paper we consider the problem of identifiability of the two-state Markovian Arrival process (MAP2). In particular, we show that the MAP2 is not identifiable and conditions are given under which two different sets of parameters, induce identical ...
Michael P. Wiper +2 more
core
Journal of Biogeography, Volume 53, Issue 6, June 2026.ABSTRACT Aim Quaternary climatic oscillations have profoundly shaped the genetic structure and geographic distributions of alpine biotas. Understanding how cold‐adapted taxa responded to past climatic shifts is essential for unravelling the processes shaping mountain biodiversity, yet cold‐adapted taxa may have followed divergent refugial histories. We
Emanuele Berrilli +2 more
wiley +1 more source
Time to ruin, insolvency penalties and dividends in a Markov-modulated multi-risk model with common shocks [PDF]
We consider a main insurance company with K subcompanies (or lines of busi- ness). The joint evolution of the surpluses of these lines of business is modeled by a Markov-modulated multivariate compound Poisson model with Poisson common shocks, modified ...
Stéphane Loisel
core
SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics
Advanced Science, Volume 13, Issue 30, 28 May 2026.ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao +11 more
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On identifiability of MAP processes [PDF]
Two types of transitions can be found in the Markovian Arrival process or MAP: with and without arrivals. In transient transitions the chain jumps from one state to another with no arrival; in effective transitions, a single arrival occurs.
Michael P. Wiper +2 more
core
Markov approximation of network traffic using hidden state models
Технічна інженеріяMarkov approximation of non-Markovian traffic is an important method for analyzing the performance of telecommunication systems where the incoming data stream has a complex correlation structure.
P.E. Pustovoitov, V.O. Kompaniets
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