Relevant bibliographies by topics / Nonasymptotic

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Nonasymptotic'

Author: Grafiati
Published: 1 June 2024

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Journal articles on the topic "Nonasymptotic"

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Berry, Kenneth J., and Paul W. Mielke. "Nonasymptotic Probability Values for Cochran's Q Statistic: A Fortran 77 Program." Perceptual and Motor Skills 82, no. 1 (1996): 303–6. http://dx.doi.org/10.2466/pms.1996.82.1.303.

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A nonasymptotic inference procedure for Cochran's Q test for the equality of matched proportions is described. An algorithm and FORTRAN 77 program are provided to compute Cochran's Q test statistic and the associated nonasymptotic probability value. The nonasymptotic method provides improvement over the usual asymptotic chi-squared analysis procedure whenever the effective number of subjects is small or the number of successes is small.
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Mielke, Paul W., and Kenneth J. Berry. "Categorical Independence Tests for Large Sparse R-Way Contingency Tables." Perceptual and Motor Skills 95, no. 2 (2002): 606–10. http://dx.doi.org/10.2466/pms.2002.95.2.606.

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A nonasymptotic chi-squared technique is shown to have very useful properties for the analysis of large sparse r-way contingency tables. Examples of analyses of 4 × 5, 5 × 6, 6 × 7. and two 2 × 2 × 2 sparse contingency tables provide comparisons of the nonasymptotic chi-squared technique with asymptotic chi-squared and exact chi-squared techniques. The asymptotic chi-squared analyses yield inflated probability values for the five tables. The nonasymptotic chi-squared technique yields probability values much closer to the exact probability values than the asymptotic chi-squared Technique for the five tables.
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Mielke, Paul W., and Kenneth J. Berry. "Nonasymptotic Inferences Based on Cochran's Q Test." Perceptual and Motor Skills 81, no. 1 (1995): 319–22. http://dx.doi.org/10.2466/pms.1995.81.1.319.

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A nonasymptotic inference procedure for Cochran's Q test for the equality of matched proportions is presented. The nonasymptotic method provides improvement over the asymptotic method when there is a small number of subjects and/or a relatively small proportion of successes for subjects.
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Tembine, Hamidou. "Nonasymptotic Mean-Field Games." IFAC Proceedings Volumes 47, no. 3 (2014): 8989–94. http://dx.doi.org/10.3182/20140824-6-za-1003.01869.

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Tembine, Hamidou. "Nonasymptotic Mean-Field Games." IEEE Transactions on Cybernetics 44, no. 12 (2014): 2744–56. http://dx.doi.org/10.1109/tcyb.2014.2315171.

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Ibrahim, Sharif, Kevin Sonnanburg, Thomas J. Asaki, and Kevin R. Vixie. "Nonasymptotic Densities for Shape Reconstruction." Abstract and Applied Analysis 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/341910.

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In this work, we study the problem of reconstructing shapes from simple nonasymptotic densities measured only along shape boundaries. The particular density we study is also known as the integral area invariant and corresponds to the area of a disk centered on the boundary that is also inside the shape. It is easy to show uniqueness when these densities are known for all radii in a neighborhood ofr=0, but much less straightforward when we assume that we only know the area invariant and its derivatives for only oner>0. We present variations of uniqueness results for reconstruction (modulo translation and rotation) of polygons and (a dense set of) smooth curves under certain regularity conditions.
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Kostina, Victoria, and Sergio Verde. "Nonasymptotic Noisy Lossy Source Coding." IEEE Transactions on Information Theory 62, no. 11 (2016): 6111–23. http://dx.doi.org/10.1109/tit.2016.2562008.

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Yang, Wei, Rafael F. Schaefer, and H. Vincent Poor. "Wiretap Channels: Nonasymptotic Fundamental Limits." IEEE Transactions on Information Theory 65, no. 7 (2019): 4069–93. http://dx.doi.org/10.1109/tit.2019.2904500.

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Ben-Yashar, Ruth, and Jacob Paroush. "A nonasymptotic Condorcet jury theorem." Social Choice and Welfare 17, no. 2 (2000): 189–99. http://dx.doi.org/10.1007/s003550050014.

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Tarantino, Angelo Marcello. "Nonasymptotic solution for antiplane cracks." Meccanica 27, no. 4 (1992): 307–10. http://dx.doi.org/10.1007/bf00424371.

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Dissertations / Theses on the topic "Nonasymptotic"

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Girard, Lucas. "Contributions to measures of segregation or polarization and to nonasymptotic inference in linear models." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAG007.

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Cette thèse se compose de deux parties indépendantes.Les trois premiers chapitres s’intéressent aux mesures de ségrégation ou polarisation. Ces notions s’appliquent à des contextes variés mais partagent une formalisation commune. Une population est divisée en deux groupes exclusifs, un groupe dit minoritaire et un majoritaire, et les individus de ces deux groupes se répartissent entre des unités ou choisissent entre des options. Les unités sont par exemple des aires résidentielles, le groupe minoritaire les individus étrangers et le groupe majoritaire les individus français pour étudier un aspect de la ségrégation résidentielle en France. Cette modélisation permet également d’étudier la polarisation du langage politique en considérant comme unités ou options les entrées d’un dictionnaire et comme groupes minoritaire et majoritaire les parlementaires de différents partis ; ici, les individus choisissent les mots qu’ils utilisent. Qualitativement, il y a de la ségrégation ou polarisation si les deux groupes tendent à choisir systématiquement des options distinctes. En ségrégation résidentielle, les individus du groupe minoritaire sont concentrés dans certaines aires géographiques au lieu d’être répartis uniformément sur le territoire. Dans l’étude du langage politique, certains mots ou expressions seront davantage prononcés par un parti que par un autre. Quantitativement, la mesure de la magnitude de la ségrégation ou polarisation est confrontée au small-unit bias.Le premier chapitre présente un programme Stata qui implémente trois méthodes permettant d’estimer des indices de ségrégation robustes au small-unit bias. Le second applique ces méthodes pour quantifier la ségrégation résidentielle en France entre 1968 et 2019 sur plusieurs dimensions (nationalité, statut social, position sur le marché du travail et proxy de l’ethnicité). Le troisième chapitre utilise les retranscriptions des débats au Congrès américain entre 1873 et 2016 pour étudier la polarisation du langage politique.La deuxième partie s’intéresse à la construction d’intervalles de confiance (IC) non-asymptotiques pour les coefficients des modèles de régression linéaire, un outil classique d’analyse économétrique. Ces intervalles reposent sur des majorations explicites de la distance entre la distribution empirique d’une somme normalisée de variables aléatoires indépendantes centrées admettant des moments d’ordre quatre et son expansion d’Edgeworth de 1er ordre. Ces majorations sont obtenues dans le quatrième chapitre, plus statistique et technique. Le cinquième et dernier chapitre utilise ces dernières pour construire des IC qui sont simultanément (i) valides pour toute taille d’échantillon (ii) sans imposer une distribution paramétrique de type Gaussienne ou l’indépendance entre régresseurs et résidus (et autorisent donc des résidus hétéroscédastiques), (iii) ayant une expression explicite, et (iv) atteignant asymptotiquement la même précision que les IC usuels fondés sur la normalité asymptotique de la statistique de Student<br>This thesis is divided into two independent parts.The first three chapters deal with measures of segregation or polarization. The notion of segregation/polarization applies to various situations, but the formal modeling remains the same. Suppose that a population of individuals, comprised of a minority and a majority group, is allocated into units or makes choices over a set of options. When studying residential, occupational, or school segregation, units can be neighborhoods, firms, classrooms, and the minority group might be immigrants versus natives. The modeling also encompasses speech polarization, for instance. The US congresspeople are divided into Democrats and Republicans; the units or options are the items of a dictionary of words or phrases, and the speakers choose which words they use. Qualitatively, there is some segregation or polarization if the allocation or choice process leads to a situation where the two groups tend to select distinct units/options. In residential segregation, the minority individuals are concentrated in some units more than in others instead of being uniformly allocated. Regarding speech polarization, the presence of polarization means that Democrats and Republicans tend to use different words or phrases when they speak in Congress. Quantitative measures of segregation/polarization struggle with the so-called ``small-unit bias.''The first chapter presents a Stata command that implements three methods to estimate segregation indices robust to ``the small-unit bias.'' The second applies these methods to quantify residential segregation in France between 1968 and 2019 along various dimensions (nationality, social status, labor market position, proxy of races). Finally, the third chapter studies speech polarization in the US Congress between 1873 and 2016 using transcripts of congressional debates.The second part of this thesis is concerned with constructing nonasymptotic confidence intervals (CIs) for the individual coefficients of a linear regression model. Linear regression models are a ubiquitous method of econometric analyses. The CIs rely on explicit upper bounds on the uniform distance between the cumulative distribution function of a standardized sum of independent centered random variables with moments of order four and its first-order Edgeworth expansion. These bounds are derived in the fourth chapter, which is more technical and closer to statistics and probability than the other chapters. The last and fifth chapter uses these results to construct CIs that, at the same time, are (i) valid for any sample size (ii) without assuming parametric assumption such as the normality of error terms or independence between covariates and error terms (hence, our CIs allow for heteroskedasticity), (iii) have a closed-form expression, and (iv) whose length is asymptotically the same as the usual CI based on the t-statistic; thus our CIs have a coverage equals to the desired nominal level in the limit when the sample size goes to infinity
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Stefani, Arno Gert [Verfasser], and Johannes [Gutachter] Huber. "Nonparametric and Nonasymptotic Confidence Intervals for Estimation of Mutual Information with Applications in Protein-Protein Docking Analysis / Arno Gert Stefani ; Gutachter: Johannes Huber." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2018. http://d-nb.info/115500616X/34.

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Balmand, Samuel. "Quelques contributions à l'estimation de grandes matrices de précision." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1024/document.

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Sous l'hypothèse gaussienne, la relation entre indépendance conditionnelle et parcimonie permet de justifier la construction d'estimateurs de l'inverse de la matrice de covariance -- également appelée matrice de précision -- à partir d'approches régularisées. Cette thèse, motivée à l'origine par la problématique de classification d'images, vise à développer une méthode d'estimation de la matrice de précision en grande dimension, lorsque le nombre $n$ d'observations est petit devant la dimension $p$ du modèle. Notre approche repose essentiellement sur les liens qu'entretiennent la matrice de précision et le modèle de régression linéaire. Elle consiste à estimer la matrice de précision en deux temps. Les éléments non diagonaux sont tout d'abord estimés en considérant $p$ problèmes de minimisation du type racine carrée des moindres carrés pénalisés par la norme $ell_1$.Les éléments diagonaux sont ensuite obtenus à partir du résultat de l'étape précédente, par analyse résiduelle ou maximum de vraisemblance. Nous comparons ces différents estimateurs des termes diagonaux en fonction de leur risque d'estimation. De plus, nous proposons un nouvel estimateur, conçu de sorte à tenir compte de la possible contamination des données par des {em outliers}, grâce à l'ajout d'un terme de régularisation en norme mixte $ell_2/ell_1$. L'analyse non-asymptotique de la convergence de notre estimateur souligne la pertinence de notre méthode<br>Under the Gaussian assumption, the relationship between conditional independence and sparsity allows to justify the construction of estimators of the inverse of the covariance matrix -- also called precision matrix -- from regularized approaches. This thesis, originally motivated by the problem of image classification, aims at developing a method to estimate the precision matrix in high dimension, that is when the sample size $n$ is small compared to the dimension $p$ of the model. Our approach relies basically on the connection of the precision matrix to the linear regression model. It consists of estimating the precision matrix in two steps. The off-diagonal elements are first estimated by solving $p$ minimization problems of the type $ell_1$-penalized square-root of least-squares. The diagonal entries are then obtained from the result of the previous step, by residual analysis of likelihood maximization. This various estimators of the diagonal entries are compared in terms of estimation risk. Moreover, we propose a new estimator, designed to consider the possible contamination of data by outliers, thanks to the addition of a $ell_2/ell_1$ mixed norm regularization term. The nonasymptotic analysis of the consistency of our estimator points out the relevance of our method
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De, lozzo Matthias. "Modèles de substitution spatio-temporels et multifidélité : Application à l'ingénierie thermique." Thesis, Toulouse, INSA, 2013. http://www.theses.fr/2013ISAT0027/document.

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Cette thèse porte sur la construction de modèles de substitution en régimes transitoire et permanent pour la simulation thermique, en présence de peu d'observations et de plusieurs sorties.Nous proposons dans un premier temps une construction robuste de perceptron multicouche bouclé afin d'approcher une dynamique spatio-temporelle. Ce modèle de substitution s'obtient par une moyennisation de réseaux de neurones issus d'une procédure de validation croisée, dont le partitionnement des observations associé permet d'ajuster les paramètres de chacun de ces modèles sur une base de test sans perte d'information. De plus, la construction d'un tel perceptron bouclé peut être distribuée selon ses sorties. Cette construction est appliquée à la modélisation de l'évolution temporelle de la température en différents points d'une armoire aéronautique.Nous proposons dans un deuxième temps une agrégation de modèles par processus gaussien dans un cadre multifidélité où nous disposons d'un modèle d'observation haute-fidélité complété par plusieurs modèles d'observation de fidélités moindres et non comparables. Une attention particulière est portée sur la spécification des tendances et coefficients d'ajustement présents dans ces modèles. Les différents krigeages et co-krigeages sont assemblés selon une partition ou un mélange pondéré en se basant sur une mesure de robustesse aux points du plan d'expériences les plus fiables. Cette approche est employée pour modéliser la température en différents points de l'armoire en régime permanent.Nous proposons dans un dernier temps un critère pénalisé pour le problème de la régression hétéroscédastique. Cet outil est développé dans le cadre des estimateurs par projection et appliqué au cas particulier des ondelettes de Haar. Nous accompagnons ces résultats théoriques de résultats numériques pour un problème tenant compte de différentes spécifications du bruit et de possibles dépendances dans les observations<br>This PhD thesis deals with the construction of surrogate models in transient and steady states in the context of thermal simulation, with a few observations and many outputs.First, we design a robust construction of recurrent multilayer perceptron so as to approach a spatio-temporal dynamic. We use an average of neural networks resulting from a cross-validation procedure, whose associated data splitting allows to adjust the parameters of these models thanks to a test set without any information loss. Moreover, the construction of this perceptron can be distributed according to its outputs. This construction is applied to the modelling of the temporal evolution of the temperature at different points of an aeronautical equipment.Then, we proposed a mixture of Gaussian process models in a multifidelity framework where we have a high-fidelity observation model completed by many observation models with lower and no comparable fidelities. A particular attention is paid to the specifications of trends and adjustement coefficients present in these models. Different kriging and co-krigings models are put together according to a partition or a weighted aggregation based on a robustness measure associated to the most reliable design points. This approach is used in order to model the temperature at different points of the equipment in steady state.Finally, we propose a penalized criterion for the problem of heteroscedastic regression. This tool is build in the case of projection estimators and applied with the Haar wavelet. We also give some numerical results for different noise specifications and possible dependencies in the observations
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Kumar, Varun. "Nonasymptotic Analysis of Massive MIMO under Different Wireless Scenarios." Thesis, 2020. http://ethesis.nitrkl.ac.in/10176/1/2020_PhD_vKumar_514EC1005_Nonasymptotic.pdf.

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The data rate demand is increasing as per Moore's law over the past two decades. This surge in data demand is a key source of motivation for the researchers to build robust wireless network and smarter wireless devices like smartphones, tabs, PCs, laptops, etc. From 2G to 4G, throughput maximization was the main driving force for the researchers of information and communication technology (ICT) industry. On the other side, energy efficiency (EE) is an essential figure of merit for the next generation (5G) wireless technology. 5G technology also improvises data rates, latency, massive connectivity, and network reliability significantly. Massive multiple-input-multiple-output (MIMO) emerges as one of the vital technologies for next-generation wireless communication. 5G technology, a base station (BS) can have hundreds or even more antenna that can improvise the spectrum efficiency (SE) and energy efficiency (EE), significantly. It can achieve all merits of conventional MIMO to a much larger scale. Despite the advantage of massive MIMO, challenges like hardware mismatch (HM), antenna correlation, pilot contamination, improper resource allocation, etc., undermine the benefits. The first part of this thesis considers a massive multi-user MIMO network, which utilizes time-division duplexing (TDD) scheme. HM is a severe concern in massive MIMO, which limits the potential of time-division multiplexing (TDD) scheme. A novel hardware calibration technique, which helps for generating the downlink (DL) channel matrix using the estimated uplink (UL) channel at a minimal computational cost, is proposed. HM causes amplitude and phase impairment in the received signal and makes the wireless channel non-reciprocal. Considering complex Gaussian hardware response at each antenna terminal of the base station (BS) or user terminal (UT) side, we derive the probability density function (PDF) of amplitude and phase mismatch are derived individually. The joint PDF of amplitude mismatch (AM) between each terminal of BS to the UT and vice-versa is also derived at a constant phase response. This joint PDF reduces the computational cost of the UT by processing signal at the BS end. The DL system performances are evaluated with the proposed algorithm under three different linear precoder like matched filter (MF), regularized zero-forcing (RZF), and zero-forcing (ZF). In the second part of this thesis considered three different antenna correlation environments based on the placement of antennas. It also considers a very large but finite number of BS antenna, and spacing between adjacent antenna elements is half of the wavelength. Using three linear detectors (maximum ratio combiner (MRC), ZF, and minimum mean square error (MMSE)), UL data rate and power efficiency in antenna correlation regime is obtained and compared to the independent and identically distributed (IID) wireless channel. Considering the impact of adjacent antenna element misalignment, for different range of degree of misalignment is also validated through the numerical simulation. In the third part of this thesis, a relay assisted cooperative network, where the base station (BS) and relay station (RS) have a very large but finite number of the antenna, is considered. An analytical expression for the UL rate in different channel conditions (perfect/imperfect) is derived, and the impact of a large number of BS and RS antenna over the UL rate is verified. Different cooperation protocol for improvising the ease of cooperative selection diversity have also been incorporated. On the other side, suitable linear precoder and decoder improvise the end-to-end SNR and end-user capacity in a dual-hop wireless network. When MIMO size increases asymptotically; the random matrix theory (RMT) helps to obtain the closed-form solution. In such a network, when statistics of the channel matrix and precoding matrix are known then, the SNR and achievable rate is easily obtained through the RMT.
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Books on the topic "Nonasymptotic"

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Lugosi, Gabor, Stephane Boucheron, and Pascal Massart. Concentration Inequalities: A Nonasymptotic Theory of Independence. Oxford University Press, 2016.

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Lugosi, Gabor, Stephane Boucheron, and Pascal Massart. Concentration Inequalities: A Nonasymptotic Theory of Independence. Oxford University Press, 2013.

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Massart, Pascal, Stéphane Boucheron, and Gábor Lugosi. Concentration Inequalities: A Nonasymptotic Theory of Independence. Oxford University Press, Incorporated, 2012.

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Book chapters on the topic "Nonasymptotic"

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Pfanzagl, Johann. "Optimality of Unbiased Estimators: Nonasymptotic Theory." In Springer Series in Statistics. Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-642-31084-3_4.

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Korzhik, Valery, and Victor Yakovlev. "Nonasymptotic estimates of information protection efficiency for the wire-tap channel concept." In Advances in Cryptology — AUSCRYPT '92. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57220-1_61.

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Łatuszyński, Krzysztof, Błażej Miasojedow, and Wojciech Niemiro. "Nonasymptotic Bounds on the Mean Square Error for MCMC Estimates via Renewal Techniques." In Monte Carlo and Quasi-Monte Carlo Methods 2010. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27440-4_31.

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Blanchard, Gilles, and Jean-Baptiste Fermanian. "Nonasymptotic One- and Two-Sample Tests in High Dimension with Unknown Covariance Structure." In Foundations of Modern Statistics. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30114-8_3.

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BAGNULS, C., and C. BERVILLIER. "NONASYMPTOTIC CRITICAL BEHAVIOR FROM FIELD THEORY." In Fluctuating Paths and Fields. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812811240_0035.

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Conference papers on the topic "Nonasymptotic"

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Kostina, Victoria, and Sergio Verdu. "Nonasymptotic noisy lossy source coding." In 2013 IEEE Information Theory Workshop (ITW 2013). IEEE, 2013. http://dx.doi.org/10.1109/itw.2013.6691295.

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Tsukerman, Igor, and Vadim Markel. "A nonasymptotic homogenization theory of electromagnetic metamaterials." In 2014 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2014. http://dx.doi.org/10.1109/iceaa.2014.6903848.

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Tsukerman, Igor, and Vadim Markel. "Nonasymptotic and nonlocal homogenization of electromagnetic metamaterials." In 2017 International Conference on Electromagnetics in Advanced Applications (ICEAA). IEEE, 2017. http://dx.doi.org/10.1109/iceaa.2017.8065535.

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Devassy, Rahul, Giuseppe Durisi, Benjamin Lindqvist, Wei Yang, and Marco Dalai. "Nonasymptotic coding-rate bounds for binary erasure channels with feedback." In 2016 IEEE Information Theory Workshop (ITW). IEEE, 2016. http://dx.doi.org/10.1109/itw.2016.7606801.

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Lee, Jaeho, Maxim Raginsky, and Pierre Moulin. "On MMSE estimation from quantized observations in the nonasymptotic regime." In 2015 IEEE International Symposium on Information Theory (ISIT). IEEE, 2015. http://dx.doi.org/10.1109/isit.2015.7282992.

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Nedic, Angelia, Alex Olshevsky, and Cesar A. Uribe. "Nonasymptotic convergence rates for cooperative learning over time-varying directed graphs." In 2015 American Control Conference (ACC). IEEE, 2015. http://dx.doi.org/10.1109/acc.2015.7172262.

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Ostman, Johan, Rahul Devassy, Giuseppe Durisi, and Erik G. Strom. "On the Nonasymptotic Performance of Variable-Length Codes with Noisy Stop Feedback." In 2019 IEEE Information Theory Workshop (ITW). IEEE, 2019. http://dx.doi.org/10.1109/itw44776.2019.8989314.

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Günlü, Onur, Matthieu Bloch, Rafael F. Schaefer, and Aylin Yener. "Nonasymptotic Performance Limits of Low-Latency Secure Integrated Sensing and Communication Systems." In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024. http://dx.doi.org/10.1109/icassp48485.2024.10448166.

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du Toit, C. F., and J. H. Cloete. "The computation of antenna electromagnetic fields at nonasymptotic distances from cylindrical near-field measurements." In International Symposium on Antennas and Propagation Society, Merging Technologies for the 90's. IEEE, 1990. http://dx.doi.org/10.1109/aps.1990.115094.

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Shcherbakov, Pavel. "The Trinomial Equation xk+l-axk + bXk-n = 0: Analysis of the Nonasymptotic Behavior of Solutions." In 2019 27th Mediterranean Conference on Control and Automation (MED). IEEE, 2019. http://dx.doi.org/10.1109/med.2019.8798544.

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