Discrete-time neural Markov models [PDF]
BMC Medical Research MethodologyBackground Markov models can be used to describe the movement of individuals between states. In medicine, Markov models are used to describe, for example, disease progression and the effects of interventions on such progression. The models can further be
Jesper Sundell +2 more
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Comparison of the flexible parametric survival model and Cox model in estimating Markov transition probabilities using real-world data. [PDF]
PLoS ONE, 2018 BACKGROUND AND OBJECTIVE:Markov micro-simulation models are being increasingly used in health economic evaluations. An important feature of the Markov micro-simulation model is its ability to consider transition probabilities of heterogeneous subgroups ...
Xudong Du +8 more
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Current recommendations on the estimation of transition probabilities in Markov cohort models for use in health care decision-making: a targeted literature review [PDF]
ClinicoEconomics and Outcomes Research, 2017 Elena Olariu,1 Kevin K Cadwell,1 Elizabeth Hancock,1 David Trueman,1 Helene Chevrou-Severac2 1PHMR Ltd, London, UK; 2Takeda Pharmaceuticals International AG, Zurich, Switzerland Objective: Although Markov cohort models represent one of the most common ...
Olariu E +4 more
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Optimal investment with time-varying transition probabilities for regime switching [PDF]
Seonmul yeongu, 2021 – This study aims to generalize the following result of McDonald and Siegel (1986) on optimal investment: it is optimal for an investor to invest when project cash flows exceed a certain threshold.
Hyo-Chan Lee +2 more
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A Note on Hidden Markov Models with Application to Criminal Intelligence
Journal of Applied Sciences and Environmental Management, 2023 Hidden Markov Models (HMMs) which fall under the class of latent variable models have received widespread attention in many fields of applications. HMMs were initially developed and applied within the context of speech recognition.
P. Osatohanmwen +6 more
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Journal of Automation and Intelligence, 2023 This paper focuses on the reachable set estimation for Markovian jump neural networks with time delay. By allowing uncertainty in the transition probabilities, a framework unifies and enhances the generality and realism of these systems. To fully exploit
Yufeng Tian, Wengang Ao, Peng Shi
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Benchmark PhotoIonization Cross-Sections of Neutral Scandium from the Ground and Excited States
Atoms, 2021 The B-spline R-matrix method has been used to investigate cross-sections for photoionization of neutral scandium from the ground and excited states in the energy region from the 3d and 4s valence electron ionization thresholds to 25 eV. The initial bound
Swaraj S. Tayal, Oleg Zatsarinny
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Branching Fractions and Transition Probabilities for UV Transitions in the Spectrum of Cr ii
The Astrophysical Journal, 2023 We present transition probabilities for 268 spectral lines of singly ionized chromium (Cr ii ) in the wavelength region 208–414 nm. Branching fractions were measured in archival Fourier transform spectra of chromium-argon and chromium-neon hollow cathode
Jacob W. Ward +5 more
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Quantum Probability’s Algebraic Origin
Entropy, 2020 Max Born’s statistical interpretation made probabilities play a major role in quantum theory. Here we show that these quantum probabilities and the classical probabilities have very different origins.
Gerd Niestegge
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Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset. [PDF]
PLoS ONE, 2016 Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users' privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries ...
Haitao Zhang +4 more
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