Results 201 to 210 of about 16,277 (238)

A Bayesian Log-Cauchy Mixture Cure Fraction Model for Heavy-Tailed Survival Data: Implementation via OpenBUGS. [PDF]

Stat Med
Salah K.
europepmc   +1 more source

Derivatives of Markov kernels and their Jordan decomposition

, 2003
Heidergott, B.F., Hordijk, A., Weisshaupt, H.   +2 more
openaire   +1 more source

Fuzzy Observables: From Weak Markov Kernels to Markov Kernels

International Journal of Theoretical Physics, 2023
AbstractWe provide a proof based on transfinite induction that every weak Markov kernel is equivalent to a Markov kernel. We only assume the space where the weak Markov kernel is defined to be second countable and metrizable. That generalizes some previous results where the kernel is required to be defined on a standard Borel space (which is second ...
Roberto Beneduci
exaly   +3 more sources

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Markov Kernels and Tribes

Information Sciences, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Anatolij Dvurečenskij
exaly   +4 more sources

Change Detection of Markov Kernels With Unknown Pre and Post Change Kernel

2022 IEEE 61st Conference on Decision and Control (CDC), 2022
7 pages, 4 ...
Jiacheng Tang
exaly   +4 more sources

High-Order Markov Kernels for Intrusion Detection

Neurocomputing, 2008
In intrusion detection systems, sequences of system calls executed by running programs can be used as evidence to detect anomalies. Markov chain is often adopted as the model in the detection systems, in which high-order Markov chain model is well suited for the detection, but as the order of the chain increases, the number of parameters of the model ...
Shengfeng Tian, Chuanhuan Yin
exaly   +3 more sources

Derivatives of Markov Kernels and Their Jordan Decomposition [PDF]

Journal of Applied Analysis, 2008
Let \((P_\vartheta)_{\vartheta \in \Theta}\) be a parametric family of Markov kernels from a measurable space \((X, \mathcal{X})\) to a locally compact space \(Y\). The family \((P_\vartheta)_{\vartheta \in \Theta}\) is called weakly differentiable at \(\vartheta\) if for any \(x \in X\) there is a finite signed Baire measure \(P'_\vartheta(x, .)\) on \
Heidergott, B.F., Hordijk, A., Weisshaupt, H.   +2 more
exaly   +4 more sources

On contraction properties of Markov kernels

Probability Theory and Related Fields, 2003
The authors study general properties of contractions of Markov kernels without assumptions on the existence of an invariant probability measure. In their previous paper [in: Séminaire de Probabilités XXXIV. Lect. Notes Math. 1729, 1-145 (2000; Zbl 0963.60040)] they have shown that the system is forgetting its initialization without nevertheless ...
Del Moral, P., Ledoux, M., Miclo, L.
openaire   +1 more source