Results 11 to 20 of about 284,348 (246)
A Theory of Stochastic Harvesting in Stochastic Environments [PDF]
We investigate how model populations respond to stochastic harvesting in a stochastic environment. In particular, we show that the effects of variable harvesting on the variance in population density and yield depend critically on the autocorrelation of environmental noise and on whether the endogenous dynamics of the population display over- or ...
Jonzén, Niclas +2 more
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In this paper, we propose a non-parametric estimator of the conditional hazard function weighted on the recursive kernel method given an explanatory variable taking values in a semi-metric space when the scalar response is censored.
Hadjer Kebir, Boubaker Mechab
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Information Bottleneck Classification in Extremely Distributed Systems
We present a new decentralized classification system based on a distributed architecture. This system consists of distributed nodes, each possessing their own datasets and computing modules, along with a centralized server, which provides probes to ...
Denis Ullmann +5 more
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Local linear modelling of the conditional distribution function for functional ergodic data
The focus of functional data analysis has been mostly on independent functional observations. It is therefore hoped that the present contribution will provide an informative account of a useful approach that merges the ideas of the ergodic theory and ...
Somia Ayad +3 more
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Bayesian model selection (BMS) and Bayesian model justifiability analysis (BMJ) provide a statistically rigorous framework for comparing competing models through the use of Bayesian model evidence (BME).
Maria Fernanda Morales Oreamuno +2 more
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Multiple-point statistics algorithms allow modeling spatial variability from training images. Among these techniques, the Direct Sampling (DS) algorithm has advanced capabilities, such as multivariate simulations, treatment of non-stationarity, multi ...
Przemysław Juda +2 more
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The distance spectrum of two new operations of graphs [PDF]
Let $G$ be a connected graph with vertex set $V(G)=\{v_1, v_2,\ldots,v_n\}$. The distance matrix $D=D(G)$ of $G$ is defined so that its $(i,j)$-entry is equal to the distance $d_G(v_i,v_j)$ between the vertices $v_i$ and $v_j$ of $G$. The eigenvalues
Zikai Tang +3 more
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We consider a kind of nonsmooth optimization problems with l1 $l_{1}$-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems.
Shouqiang Du, Miao Chen
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Local linear approach: Conditional density estimate for functional and censored data
Let YY be a random real response, which is subject to right censoring by another random variable CC. In this paper, we study the nonparametric local linear estimation of the conditional density of a scalar response variable and when the covariable takes ...
Benkhaled Abdelkader, Madani Fethi
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This article presents a novel approach to integrate a throughput prediction model for the ball mill into short-term stochastic production scheduling in mining complexes.
Christian Both, Roussos Dimitrakopoulos
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