Robust adaptive efficient estimation for semi-Markov nonparametric regression models

We consider the nonparametric robust estimation problem for regression models in continuous time with semi-Markov noises. An adaptive model selection procedure is proposed. Under general moment conditions on the noise distribution a sharp non-asymptotic oracle inequality for the robust risks is obtained and the robust efficiency is shown. It turns out that for semi-Markov models the robust minimax convergence rate may be faster or slower than the classical one

Robust adaptive efficient estimation for a semi-Markov continuous time regression from discrete data

In this article we consider the nonparametric robust estimation problem for regression models in continuous time with semi-Markov noises observed in discrete time moments. An adaptive model selection procedure is proposed. A sharp non-asymptotic oracle inequality for the robust risks is obtained. We obtain sufficient conditions on the frequency observations under which the robust efficiency is shown. It turns out that for the semi-Markov models the robust minimax convergence rate may be faster or slower than the classical one.Comment: arXiv admin note: text overlap with arXiv:1604.0451

Considerations on replacing and suspending disciplinary sanctions. The issue of granting compensation for ungrounded or unlawful disciplinary sanctions

Court's ability to replace the disciplinary sanction imposed by the employer with an easier one is the power to individualize employee's disciplinary sanction imposed by the general statutory criteria – the circumstances of committing the crime, the degree of culpability of the employee consequences of a disciplinary offence, the general behaviour of the employee and any disciplinary sanctions previously incurred. Another issue under discussion and which was not brought about a unified point of view is about the possibility of temporary suspension of disciplinary decision enforcement, pending resolution of the challenge which the court was invested with. This is why it's necessary the intervention of the legislator as statuary express the legal nature of the disciplinary decision. In all cases where the court ordered the annulment of illegality punish the employee who suffered an injury will receive compensation under article 52, paragraph 2, article 78 or, where appropriate, article 269 paragraph 1 of the Labour Code

Analyzing domain shift when using additional data for the MICCAI KiTS23 Challenge

Using additional training data is known to improve the results, especially for medical image 3D segmentation where there is a lack of training material and the model needs to generalize well from few available data. However, the new data could have been acquired using other instruments and preprocessed such its distribution is significantly different from the original training data. Therefore, we study techniques which ameliorate domain shift during training so that the additional data becomes better usable for preprocessing and training together with the original data. Our results show that transforming the additional data using histogram matching has better results than using simple normalization.Comment: This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in [TODO], and is available online at https://doi.org/[TODO

Robust adaptive efficient estimation for semi-Markov nonparametric regression models

International audienceWe consider the nonparametric robust estimation problem for regression models in continuous time with semi-Markov noises. An adaptive model selection procedure is proposed. Under general moment conditions on the noise distribution a sharp non-asymptotic oracle inequality for the robust risks is obtained and the robust efficiency is shown. It turns out that for semi-Markov models the robust minimax convergence rate may be faster or slower than the classical one

Intelligent Control of a Distributed Energy Generation System Based on Renewable Sources

The control of low power systems, which include renewable energy sources, a local network, an electrochemical storage subsystem and a grid connection, is inherently hierarchical. The lower level consists of the wind energy sources (power limitation at rated value in full load regime and energy optimization in partial load regime) and photovoltaic (energy conversion optimization) control systems. The present paper deals with control problem at the higher level and aims at generating the control solution for the energetic transfer between the system components, given that the powers of the renewable energy sources and the power in the local network have random characteristics. For the higher level, the paper proposes a mixed performance criterion, which includes an energy sub-criterion concerning the costs of electricity supplied to local consumers, and a sub-criterion related to the lifetime of the battery. Three variants were defined for the control algorithm implemented by using fuzzy logic techniques, in order to control the energy transfer in the system. Particular attention was given to developing the models used for the simulation of the distributed energy system components and to the whole control system, given that the objective is not the real-time optimization of the criterion, but to establish by numerical simulation in the design stage the "proper" parameters of the control system. This is done by taking into account the multi-criteria performance objective when the power of renewable energy sources and the load have random characteristics

SMM: An R Package for Estimation and Simulation of Discrete-time semi-Markov Models

International audienceSemi-Markov models, independently introduced by Lévy (1954), Smith (1955) and Takacs (1954), are a generalization of the well-known Markov models. For semi-Markov models, sojourn times can be arbitrarily distributed, while sojourn times of Markov models are constrained to be exponentially distributed (in continuous time) or geometrically distributed (in discrete time). The aim of this paper is to present the R package SMM, devoted to the simulation and estimation of discrete-time multi-state semi-Markov and Markov models. For the semi-Markov case we have considered: parametric and non-parametric estimation; with and without censoring at the beginning and/or at the end of sample paths; one or several independent sample paths. Several discrete-time distributions are considered for the parametric estimation of sojourn time distributions of semi-Markov chains: Uniform, Geometric, Poisson, Discrete Weibull and Binomial Negative

Estimation of the stationary distribution of a semi-Markov chain

This article is concerned with the estimation of the stationary distribution of a discretetime semi-Markov process. After briefly presenting the discrete-time semi-Markov setting, wepropose an estimator of the associated stationary distribution. The main results concern theasymptotic properties of this estimator, as the sample size becomes large. A numerical exampleillustrates the asymptotic properties of the estimators