Academic literature on the topic 'Distributions à queues lourdes'
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Journal articles on the topic "Distributions à queues lourdes"
Tahiananirina, RAZAFINDRALAMBO Hasina, RAZAFIMANDIMBY Honoré, RAMAHAZOSOA Irrish Parker, RABEHARISOA Jean Marc, and RATIARISON Adolphe Andriamanga. "Estimations Des Quantiles Extrêmes Des Précipitations Convectives Avec Les Distributions des Valeurs Extrêmes Généralisées : Cas Des Plaines De La Basse Betsiboka." International Journal of Progressive Sciences and Technologies 40, no. 1 (August 30, 2023): 308. http://dx.doi.org/10.52155/ijpsat.v40.1.5578.
Full textSzczotka, Władysław. "Stationary representation of queues. I." Advances in Applied Probability 18, no. 3 (September 1986): 815–48. http://dx.doi.org/10.2307/1427189.
Full textSzczotka, Władysław. "Stationary representation of queues. I." Advances in Applied Probability 18, no. 03 (September 1986): 815–48. http://dx.doi.org/10.1017/s0001867800016086.
Full textChaudhry, Mohan L., Indra, and Vijay Rajan. "Analytically Simple and Computationally Efficient Solution to Geo/G/1 and Geo/G/1/N Queues Involving Heavy-tailed Distributions for Service Times." Calcutta Statistical Association Bulletin 70, no. 1 (May 2018): 74–85. http://dx.doi.org/10.1177/0008068318770566.
Full textKarpelevitch, F. I., and A. Ya Kreinin. "Joint distributions in Poissonian tandem queues." Queueing Systems 12, no. 3-4 (September 1992): 273–86. http://dx.doi.org/10.1007/bf01158803.
Full textTaylor, Nicholas B., and Benjamin G. Heydecker. "Estimating probability distributions of dynamic queues." Transportation Planning and Technology 38, no. 1 (November 20, 2014): 3–27. http://dx.doi.org/10.1080/03081060.2014.976987.
Full textWang, P. Patrick, and Vicky F. Locker. "Steady-State Distributions Of Parallel Queues." INFOR: Information Systems and Operational Research 39, no. 1 (February 2001): 89–106. http://dx.doi.org/10.1080/03155986.2001.11732428.
Full textMiyazawa, Masakiyo, and Ronald W. Wolff. "Symmetric queues with batch departures and their networks." Advances in Applied Probability 28, no. 1 (March 1996): 308–26. http://dx.doi.org/10.2307/1427923.
Full textMiyazawa, Masakiyo, and Ronald W. Wolff. "Symmetric queues with batch departures and their networks." Advances in Applied Probability 28, no. 01 (March 1996): 308–26. http://dx.doi.org/10.1017/s0001867800027385.
Full textHunter, Jeffrey J. "Filtering of Markov renewal queues, IV: Flow processes in feedback queues." Advances in Applied Probability 17, no. 2 (June 1985): 386–407. http://dx.doi.org/10.2307/1427147.
Full textDissertations / Theses on the topic "Distributions à queues lourdes"
Rivoire, Manon. "Risk measures in finance, Backtesting, Sensitivity and Robustness." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAX042.
Full textIn Chapter 1, we focus on two time transformations: the time-translation and the time-scaling and on the related properties called the stationarity and the self-similarity. We prove the stationarity and self-similarity properties of the processes first in a the very general framework of the Hilbert spaces; then in a the more specific framework of the the Gaussian Hilbert space where the properties are proved in distribution (weak sense) and in a trajectory sense (strict sense). We also provide examples of such processes called standard Brownian motion and fractional Brownian motion (fBm), in the univariate and multivariate frameworks (mfBm). In Chapter 2, we propose to describe price trajectories using fractional geometric Brownian motions. This allows adding correlations between logarithmic returns to express long-range dependency. Logarithmic returns are then described using self-similar Gaussian processes with stationary and correlated increments, the fBm's and mfBm's. In this framework, risk measures that are based on the loss distribution, can then be accurately predicted taking into account the long-range dependency. We focus on predicting the most commonly used risk measure by regulators, called Value-at-Risk (VaR). We introduce a model that provides a Gaussian approximation of Value-at-Risk (VaR) for the assets portfolio under fractional dynamics (mfBm). We provide a quantification of the error of approximation and we carry out backtesting experiments on simulated and market data. In Chapter 3, we propose to model the loss distribution with a heavy-tailed distribution that better takes into account the extreme events, called the Pareto distribution that presents interesting properties of scaling and stability by conditioning and to replace VaR by Expected-Shortfall which is more sensitive to the tail risk. The objective is to explore non-asymptotic robust methods for estimating ES in heavy-tailed distributions such that the Median-of-Means, the Trimmed-Means, and the Lee-Valiant estimators that we compare to the empirical mean estimator (asymptotic). We study their bias and their convergence rate
Aleiyouka, Mohalilou. "Sur la dépendance des queues de distributions." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMLH28/document.
Full textThe modeling of the dependence between several variables can focus either on the positive or negative correlation between the variables, or on other more effective ways, which determine the tails dependence of distributions.In this thesis, we are interested in the tail dependence of distributions, by presenting some properties and results. Firstly, we obtain the limit tail dependence coefficient for the generalized hyperbolic law according to different parameter values of this law. Then, we exhibit some properties and results of die extremal dependence coefficient in the case where the random variables follow a unitary Fréchet law.Finally, we present a Real Time Database ManagementSystems (RDBMS). The goal is to propose probabilistic models to study thebehavior of real-time transactions, in order to optimize its performance
Joly, Emilien. "Estimation robuste pour des distributions à queue lourde." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLS216/document.
Full textIn this thesis, we are interested in estimating the mean of heavy-tailed random variables. We focus on a robust estimation of the mean approach as an alternative to the classical empirical mean estimation. The goal is to develop sub-Gaussian concentration inequalities for the estimating error. In other words, we seek strong concentration results usually obtained for bounded random variables, in the context where the bounded condition is replaced by a finite variance condition. Two existing estimators of the mean of a real-valued random variable are invoked and their concentration results are recalled. Several new higher dimension adaptations are discussed. Using those estimators, we introduce a new version of empirical risk minimization for heavy-tailed random variables. Some applications are developed. These results are illustrated by simulations on artificial data samples. Lastly, we study the multivariate case in the U-statistics context. A natural generalization of existing estimators is offered, once again, by previous estimators
Worms, Rym. "Vitesses de convergence pour l'approximation des queues de distributions." Université de Marne-la-Vallée, 2000. http://www.theses.fr/2000MARN0091.
Full textThe aim of this thesis is to provide some rates of convergence for the Generalized Pareto approximation of the excesses. In the first chapter, we determine the rate of uniform convergence of the distribution of the excesses, suitably normalized, towards its Generalized Pareto limit, using first and second order conditions that ensure that the distribution we consider lies in one of the three maximum domains of attraction. The second chapter is devoted to the study of the relative approximation error of a high quatile by the quantile of the Generalized Pareto limit, for distributions in the Fréchet or the Gumbel maximum domain of attraction, with infinite end-point. We provide sufficient conditions on the order of the considered quantile and the threshold that we use to define the excesses, in order to ensure that this relative error tends to 0. In the third chapter, we provide conditions for a penultimate approximation of the excesses to exist. In other words, we look for a sequence of Generalised Pareto Distributions that approximate the excesses better than the ultimate one. We study the uniform rate of convergence of the distribution of the excesses towards its penultimate approximation
Brahimi, Mammar. "Approximating multi-server queues with inhomgeneous arrival rates and continuous service time distributions." Thesis, Lancaster University, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.254028.
Full textChang, Emmanuel. "QCD sur réseaux et les propriétés des mésons lourd-légers : les distributions radiales dans les mésons lourd-légers et le mélange Bº-B̄º dans la limite statique." Paris 7, 2009. http://www.theses.fr/2009PA077204.
Full textPhenomenology of the heavy-light mesons is investigated by using QCD simulations on the lattice. The work is particularly focused on the light quark dynamics in the heavy-light Systems when the heavy quark is infinitely heavy. The mass splitting between the excited and the lowest lying states has been studied with the unquenched lattice data containing SN__f=2S dynamical light quarks. A very high accuracy of the lattice results for the coupling to the pions is achieved through several improvements over previous lattice computations of these couplings. Moreover, the present study provides a new method which allows for the first lattice determination of the pion emission in the transition between the first excited and the lowest lying heavy-light meson. These couplings are necessary ingredients for the description of heavy-light mesons by an effective theory known as the Heavy Meson Chiral Perturbation Theory. They are also essential in the chiral extrapolations of the lattice results for the quantities which are relevant to the SBS-physics phenomenology. Special attention is devoted to the improvement of the technique of Computing the static heavy quark propagator on the lattice by using the hyper-cubic blocking techniques (HYP). We then make a detailed study of the matrix elements of ail parity conserving four-quark S\Delta B=2S operators which enter the theoretical description of the SB~0S-S\bar B~0S mixing amplitude in the Standard Model, and in its supersymmetric extensions. This is the first such study with HYP-blocked Wilson lines, which provides us with an extra benefit: the spurious mixing of operators computed on the lattice is much smaller with respect to what has been done in the past. Renormalization and matching of Heavy Quark Effective Theory on the lattice to the continuum QCD is made by using boosted perturbation theory. A short discussion of impact of our results on the SBS-physics phenomenology is provided too
Lekina, Alexandre. "Estimation non-paramétrique des quantiles extrêmes conditionnels." Phd thesis, Grenoble, 2010. http://www.theses.fr/2010GRENM065.
Full textThe main goal of this thesis is to propose new estimators of extreme quantiles in the conditional case, that is to say in the situation where the variable of interest Y, supposed to be random and real, is recorded simultaneously with some covariate information X. To this aim, we focus on the case where the conditional distribution of Y given X = x is “heavy-tailed”. Two situations are considered. First, when the covariate is deterministic and finite-dimensional or infinite-dimensional (i. E functional covariate), we propose to estimate the extreme quantiles by the “moving window approach“. The asymptotic distribution of the proposed estimators is given in the case where the quantile is in the range of data or near and even beyond the sample. Next, when the covariate is random and finite-dimensional, we show that under some conditions, it is possible to estimate these extreme quantiles using a kernel estimator of the conditional survival function. As a consequence, this result allows us to introduce two smooth versions of the conditional tail index estimator necessary to extrapolate. Asymptotic distributions of these estimators are established. Furthermore, we also considered the case without covariate. When the underlying, the cumulative distribution function is “heavy-tailed”. A new unconditional extreme quantile estimator is introduced and studied. To assess the behavior of all our new statistical tools, numerical experiments on simulated data are provided and illustrations on real datasets are presented
Lekina, Alexandre. "Estimation non-paramétrique des quantiles extrêmes conditionnels." Phd thesis, Université de Grenoble, 2010. http://tel.archives-ouvertes.fr/tel-00529476.
Full textMethni, Jonathan El. "Contributions à l'estimation de quantiles extrêmes. Applications à des données environnementales." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM035/document.
Full textThis thesis can be viewed within the context of extreme value statistics. It provides two main contributions to this subject area. In the recent literature on extreme value statistics, a model on tail distributions which encompasses Pareto-type distributions as well as Weibull tail-distributions has been introduced. The two main types of decreasing of the survival function are thus modeled. An estimator of extreme quantiles has been deduced from this model, but it depends on two unknown parameters, making it useless in practical situations. The first contribution of this thesis is to propose estimators of these parameters. Plugging our estimators in the previous extreme quantiles estimator allows us to estimate extreme quantiles from Pareto-type and Weibull tail-distributions in an unified way. The asymptotic distributions of our three new estimators are established and their efficiency is illustrated on a simulation study and on a real data set of exceedances of the Nidd river in the Yorkshire (England). The second contribution of this thesis is the introduction and the estimation of a new risk measure, the so-called Conditional Tail Moment. It is defined as the moment of order a>0 of the loss distribution above the quantile of order p in (0,1) of the survival function. Estimating the Conditional Tail Moment permits to estimate all risk measures based on conditional moments such as the Value-at-Risk, the Conditional Tail Expectation, the Conditional Value-at-Risk, the Conditional Tail Variance or the Conditional Tail Skewness. Here, we focus on the estimation of these risk measures in case of extreme losses i.e. when p converges to 0 when the size of the sample increases. It is moreover assumed that the loss distribution is heavy-tailed and depends on a covariate. The estimation method thus combines nonparametric kernel methods with extreme-value statistics. The asymptotic distribution of the estimators is established and their finite sample behavior is illustrated both on simulated data and on a real data set of daily rainfalls in the Cévennes-Vivarais region (France)
Loiseau, Patrick. "Contributions à l'analyse des lois d'échelles et de la qualité de service dans les réseaux : aspects expérimentaux et théoriques." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2009. http://tel.archives-ouvertes.fr/tel-00533073.
Full textBooks on the topic "Distributions à queues lourdes"
Adlouni, Salaheddine El. Caractérisation des distributions à queue lourde pour l'analyse des crues. Québec: INRS-ETE, 2007.
Find full textLiu, Yunan. Many-Server Queues with Time-Varying Arrivals, Customer Abandonment, and non-Exponential Distributions. [New York, N.Y.?]: [publisher not identified], 2011.
Find full textProbability and Distributions: With Approximation Studies on Queues. New Delhi, India: South Asian Publishers Pvt. Ltd., 2002.
Find full textKing, Russell Edward. Sojourn distributions for particular customers in networks of queues. 1986.
Find full textBook chapters on the topic "Distributions à queues lourdes"
Grottke, Michael, Varsha Apte, Kishor S. Trivedi, and Steve Woolet. "Response Time Distributions in Networks of Queues." In International Series in Operations Research & Management Science, 587–641. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-6472-4_14.
Full textShortle, John, Donald Gross, Martin J. Fischer, and Denise M. B. Masi. "Numerical Methods for Analyzing Queues with Heavy-Tailed Distributions." In Operations Research/Computer Science Interfaces Series, 193–206. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3762-2_10.
Full textSchassberger, R. "Exact Results on Response Time Distributions in Networks of Queues." In Messung, Modellierung und Bewertung von Rechensystemen, 115–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-87472-7_9.
Full textBraband, Jens. "Waiting time distributions for processor sharing queues with state-dependent arrival and service rates." In Computer Performance Evaluation Modelling Techniques and Tools, 111–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58021-2_6.
Full textBraband, Jens, and Rolf Schaßberger. "Random Quantum Allocation: A new approach to waiting time distributions for M/M/N processor sharing queues." In Messung, Modellierung und Bewertung von Rechen- und Kommunikationssystemen, 130–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78495-8_11.
Full textD. KOUVATSOS, Demetres, and Ismail A. MAGEED. "Formalismes de maximum d’entropie non extensive et inférence inductive d’une file d’attente M/G/1 stable à queues lourdes." In Théorie des files d’attente 2, 183–213. ISTE Group, 2021. http://dx.doi.org/10.51926/iste.9004.ch5.
Full textGrimmett, Geoffrey R., and David R. Stirzaker. "Queues." In Probability and Random Processes, 440–70. Oxford University PressOxford, 2001. http://dx.doi.org/10.1093/oso/9780198572237.003.0011.
Full text"Joint and Conditional Distributions." In Probability, Markov Chains, Queues, and Simulation, 64–86. Princeton University Press, 2009. http://dx.doi.org/10.2307/j.ctvcm4gtc.7.
Full text"Chapter 4. Joint and Conditional Distributions." In Probability, Markov Chains, Queues, and Simulation, 64–86. Princeton University Press, 2009. http://dx.doi.org/10.1515/9781400832811-005.
Full textMEDHI, J. "Queues with General Arrival Time and Service-Time Distributions." In Stochastic Models in Queueing Theory, 339–73. Elsevier, 2003. http://dx.doi.org/10.1016/b978-012487462-6/50007-2.
Full textConference papers on the topic "Distributions à queues lourdes"
Ciucu, Florin, Felix Poloczek, and Amr Rizk. "Queue and Loss Distributions in Finite-Buffer Queues." In SIGMETRICS '19: ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3309697.3331496.
Full textHarrison, P. G., and H. Zatschler. "Sojourn time distributions in modulated G-queues with batch processing." In First International Conference on the Quantitative Evaluation of Systems, 2004. QEST 2004. Proceedings. IEEE, 2004. http://dx.doi.org/10.1109/qest.2004.1348023.
Full textSnyder, Patricia M., and William J. Stewart. "An approximate numerical solution for multiclass preemptive priority queues with general service time distributions." In the 1985 ACM SIGMETRICS conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/317795.317820.
Full textKonovalov, Mikhail, and Rostislav Razumchik. "Minimizing Mean Response Time In Batch-Arrival Non-Observable Systems With Single-Server FIFO Queues Operating In Parallel." In 35th ECMS International Conference on Modelling and Simulation. ECMS, 2021. http://dx.doi.org/10.7148/2021-0272.
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