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pro vyhledávání: '"Moesching, Alexandre"'
Hidden Markov models (HMMs) are characterized by an unobservable (hidden) Markov chain and an observable process, which is a noisy version of the hidden chain. Decoding the original signal (i.e., hidden chain) from the noisy observations is one of th
Externí odkaz:
http://arxiv.org/abs/2305.18578
Autor:
Duembgen, Lutz, Moesching, Alexandre
Publikováno v:
ESAIM: Probability and Statistics 2023
The usual stochastic order and the likelihood ratio order between probability distributions on the real line are reviewed in full generality. In addition, for the distribution of a random pair $(X,Y)$, it is shown that the conditional distributions o
Externí odkaz:
http://arxiv.org/abs/2209.07868
Autor:
Mösching, Alexandre, Dümbgen, Lutz
Consider bivariate observations $(X_1,Y_1), \ldots, (X_n,Y_n) \in \mathbb{R}\times \mathbb{R}$ with unknown conditional distributions $Q_x$ of $Y$, given that $X = x$. The goal is to estimate these distributions under the sole assumption that $Q_x$ i
Externí odkaz:
http://arxiv.org/abs/2007.11521
Publikováno v:
Methodology and Computing in Applied Probability 24 (2022), 2633-2645
In the context of estimating stochastically ordered distribution functions, the pool-adjacent-violators algorithm (PAVA) can be modified such that the computation times are reduced substantially. This is achieved by studying the dependence of antiton
Externí odkaz:
http://arxiv.org/abs/2006.05527
Autor:
Mösching, Alexandre, Duembgen, Lutz
We consider bivariate observations $(X_1,Y_1), \ldots, (X_n,Y_n)$ such that, conditional on the $X_i$, the $Y_i$ are independent random variables with distribution functions $F_{X_i}$, where $(F_x)_x$ is an unknown family of distribution functions. U
Externí odkaz:
http://arxiv.org/abs/1901.02398
In many instances, imposing a constraint on the shape of a density is a reasonable and flexible assumption. It offers an alternative to parametric models which can be too rigid and to other nonparametric methods requiring the choice of tuning paramet
Externí odkaz:
http://arxiv.org/abs/1808.09340
Publikováno v:
In Computational Statistics and Data Analysis November 2021 163
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