Relevant bibliographies by topics / Distributional

Contents

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

Academic literature on the topic 'Distributional'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Distributional"

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Fu, Heman, Jincheng Xiong, and Huoyun Wang. "The Hierarchy of Distributional Chaos." International Journal of Bifurcation and Chaos 25, no. 01 (January 2015): 1550001. http://dx.doi.org/10.1142/s0218127415500017.

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For each λ ∈ [0, 1], λ-power distributional chaos has been defined via Furstenberg families to strengthen distributional chaos. For the sake of distinguishing them, we present a class of dynamical systems, called wedge-shape systems. Through a thorough analysis of dynamical behaviors of all point-pairs, we show that wedge-shape systems can be λ-power distributionally chaotic and admit no λ′-power distributionally scrambled pairs for any λ′ ∈ [0, λ). Then we unfold a picture of distributional chaos with rich hierarchical structures, which helps to improve our comprehension of the diversity of chaos.
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Wang, Lidong, Xiang Wang, Fengchun Lei, and Heng Liu. "Asymptotic average shadowing property, almost specification property and distributional chaos." Modern Physics Letters B 30, no. 03 (January 28, 2016): 1650001. http://dx.doi.org/10.1142/s0217984916500019.

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It is proved that a nontrivial compact dynamical system with asymptotic average shadowing property (AASP) displays uniformly distributional chaos or distributional chaos in a sequence. Moreover, distributional chaos in a system with AASP can be uniform and dense in the measure center, that is, there is an uncountable uniformly distributionally scrambled set consisting of such points that the orbit closure of every point contains the measure center. As a corollary, the similar results hold for the system with almost specification property.
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Wang, Lidong, Yingcui Zhao, Yuelin Gao, and Heng Liu. "Chaos to Multiple Mappings." International Journal of Bifurcation and Chaos 27, no. 08 (July 2017): 1750119. http://dx.doi.org/10.1142/s021812741750119x.

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Let [Formula: see text] be a compact metric space and [Formula: see text] be an [Formula: see text]-tuple of continuous selfmaps on [Formula: see text]. This paper investigates Hausdorff metric Li–Yorke chaos, distributional chaos and distributional chaos in a sequence from a set-valued view. On the basis of this research, we draw the main conclusions as follows: (i) If [Formula: see text] has a distributionally chaotic pair, especially [Formula: see text] is distributionally chaotic, the strongly nonwandering set [Formula: see text] contains at least two points. (ii) We give a sufficient condition for [Formula: see text] to be distributionally chaotic in a sequence and chaotic in the strong sense of Li–Yorke. Finally, an example to verify (ii) is given.
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Weeds, Julie, and David Weir. "Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity." Computational Linguistics 31, no. 4 (December 2005): 439–75. http://dx.doi.org/10.1162/089120105775299122.

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Techniques that exploit knowledge of distributional similarity between words have been proposed in many areas of Natural Language Processing. For example, in language modeling, the sparse data problem can be alleviated by estimating the probabilities of unseen co-occurrences of events from the probabilities of seen co-occurrences of similar events. In other applications, distributional similarity is taken to be an approximation to semantic similarity. However, due to the wide range of potential applications and the lack of a strict definition of the concept of distributional similarity, many methods of calculating distributional similarity have been proposed or adopted. In this work, a flexible, parameterized framework for calculating distributional similarity is proposed. Within this framework, the problem of finding distributionally similar words is cast as one of co-occurrence retrieval (CR) for which precision and recall can be measured by analogy with the way they are measured in document retrieval. As will be shown, a number of popular existing measures of distributional similarity are simulated with parameter settings within the CR framework. In this article, the CR framework is then used to systematically investigate three fundamental questions concerning distributional similarity. First, is the relationship of lexical similarity necessarily symmetric, or are there advantages to be gained from considering it as an asymmetric relationship? Second, are some co-occurrences inherently more salient than others in the calculation of distributional similarity? Third, is it necessary to consider the difference in the extent to which each word occurs in each co-occurrence type? Two application-based tasks are used for evaluation: automatic thesaurus generation and pseudo-disambiguation. It is possible to achieve significantly better results on both these tasks by varying the parameters within the CR framework rather than using other existing distributional similarity measures; it will also be shown that any single unparameterized measure is unlikely to be able to do better on both tasks. This is due to an inherent asymmetry in lexical substitutability and therefore also in lexical distributional similarity.
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Duchi, John C., Peter W. Glynn, and Hongseok Namkoong. "Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach." Mathematics of Operations Research 46, no. 3 (August 2021): 946–69. http://dx.doi.org/10.1287/moor.2020.1085.

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We study statistical inference and distributionally robust solution methods for stochastic optimization problems, focusing on confidence intervals for optimal values and solutions that achieve exact coverage asymptotically. We develop a generalized empirical likelihood framework—based on distributional uncertainty sets constructed from nonparametric f-divergence balls—for Hadamard differentiable functionals, and in particular, stochastic optimization problems. As consequences of this theory, we provide a principled method for choosing the size of distributional uncertainty regions to provide one- and two-sided confidence intervals that achieve exact coverage. We also give an asymptotic expansion for our distributionally robust formulation, showing how robustification regularizes problems by their variance. Finally, we show that optimizers of the distributionally robust formulations we study enjoy (essentially) the same consistency properties as those in classical sample average approximations. Our general approach applies to quickly mixing stationary sequences, including geometrically ergodic Harris recurrent Markov chains.
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Beare, Brendan K. "Distributional Replication." Entropy 23, no. 8 (August 17, 2021): 1063. http://dx.doi.org/10.3390/e23081063.

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A function which transforms a continuous random variable such that it has a specified distribution is called a replicating function. We suppose that functions may be assigned a price, and study an optimization problem in which the cheapest approximation to a replicating function is sought. Under suitable regularity conditions, including a bound on the entropy of the set of candidate approximations, we show that the optimal approximation comes close to achieving distributional replication, and close to achieving the minimum cost among replicating functions. We discuss the relevance of our results to the financial literature on hedge fund replication; in this case, the optimal approximation corresponds to the cheapest portfolio of market index options which delivers the hedge fund return distribution.
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Kroese, A. H., E. A. Meulen, K. Poortema, and W. Schaafsma. "Distributional inference." Statistica Neerlandica 49, no. 1 (March 1995): 63–82. http://dx.doi.org/10.1111/j.1467-9574.1995.tb01455.x.

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Bonilla, Antonio, and Marko Kostić. "Reiterative Distributional Chaos on Banach Spaces." International Journal of Bifurcation and Chaos 29, no. 14 (December 26, 2019): 1950201. http://dx.doi.org/10.1142/s0218127419502018.

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If we change the upper and lower densities in the definition of distributional chaos of a continuous linear operator on a Banach space [Formula: see text] by the Banach upper and Banach lower densities, respectively, we obtain Li–Yorke chaos. Motivated by this, we introduce the notions of reiterative distributional chaos of types [Formula: see text], [Formula: see text] and [Formula: see text] for continuous linear operators on Banach spaces, which are characterized in terms of the existence of an irregular vector with additional properties. Moreover, we study its relations with other dynamical properties and present the conditions for the existence of a vector subspace [Formula: see text] of [Formula: see text], such that every nonzero vector in [Formula: see text] is both irregular for [Formula: see text] and distributionally near zero for [Formula: see text].
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DE BOLLA, PETER, EWAN JONES, PAUL NULTY, GABRIEL RECCHIA, and JOHN REGAN. "Distributional Concept Analysis." Contributions to the History of Concepts 14, no. 1 (June 1, 2019): 66–92. http://dx.doi.org/10.3167/choc.2019.140104.

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This article proposes a novel computational method for discerning the structure and history of concepts. Based on the analysis of co-occurrence data in large data sets, the method creates a measure of “binding” that enables the construction of verbal constellations that comprise the larger units, “concepts,” that change over time. In contrast to investigation into semantic networks, our method seeks to uncover structures of conceptual operation that are not simply semantic. These larger units of lexical operation that are visualized as interconnected networks may have underlying rules of formation and operation that have as yet unexamined—perhaps tangential—connection to meaning as such. The article is thus exploratory and intended to open the history of concepts to some new avenues of investigation.
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Bruni, E., N. K. Tran, and M. Baroni. "Multimodal Distributional Semantics." Journal of Artificial Intelligence Research 49 (January 23, 2014): 1–47. http://dx.doi.org/10.1613/jair.4135.

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Distributional semantic models derive computational representations of word meaning from the patterns of co-occurrence of words in text. Such models have been a success story of computational linguistics, being able to provide reliable estimates of semantic relatedness for the many semantic tasks requiring them. However, distributional models extract meaning information exclusively from text, which is an extremely impoverished basis compared to the rich perceptual sources that ground human semantic knowledge. We address the lack of perceptual grounding of distributional models by exploiting computer vision techniques that automatically identify discrete “visual words” in images, so that the distributional representation of a word can be extended to also encompass its co-occurrence with the visual words of images it is associated with. We propose a flexible architecture to integrate text- and image-based distributional information, and we show in a set of empirical tests that our integrated model is superior to the purely text-based approach, and it provides somewhat complementary semantic information with respect to the latter.
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Dissertations / Theses on the topic "Distributional"

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Schluter, Christian. "Topics in distributional analysis : the importance of intermediate institutions for income distributions, inequality and intra-distributional mobility." Thesis, London School of Economics and Political Science (University of London), 1999. http://etheses.lse.ac.uk/1487/.

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The unifying theme of this dissertation is the importance of intermediate institutions for income distributions, inequality and intra-distributional mobility. First, we analyse the effects of informational problems in a general equilibrium model with dynamically evolving wealth distributions. Poor agents need to borrow funds but a non-commitment problem on the capital market leads to persistent inequality. The next important institution to be examined is the tax-benefit system. The third chapter investigates the relative performance of alternative unemployment benefit regimes in a search-theoretic general equilibrium model of the labour market. Policy objectives such as the reduction in inequality or the alleviation of poverty are considered and the incentive problems are examined. Prior to the empirical analysis, the fourth chapter develops the large sample distribution of a number of inequality and mobility indices. Moreover, the relative performance of these (asymptotic) approximations and various bootstrap estimators is examined. The data is described in chapter five. The sixth chapter analyses the distributional consequences of the German tax-benefit system using the German Socio-Economic Panel. Two dimensions income dynamics are investigated by distinguishing between shape dynamics and intra-distributional mobility. The complementarity between various tools such as non-parametric stochastic kernel density estimates and transition matrices is explored. As the transition probabilities are found to be time-varying, several statistical models of income mobility are estimated (and a new mover-stayer model is proposed) in the last chapter. In order to give an economic explanation of the observed mobility patterns various duration models (with duration dependent hazards and unobserved heterogeneity) are estimated.
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King, Robert Arthur Ravenscroft. "New distributional fitting methods applied to the generalised [lambda] distribution." Thesis, Queensland University of Technology, 1999.

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Haili, Hailiza Kamarul. "Distributional problems in arithmetic." Thesis, University of Liverpool, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366245.

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Baker, Kirk. "Multilingual Distributional Lexical Similarity." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1221752517.

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Trenn, Stephan. "Distributional differential algebraic equations." Ilmenau Univ.-Verl, 2009. http://d-nb.info/99693197X/04.

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Bilyk, Dmytro. "Distributional estimates for multilinear operators." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4139.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2005.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (May 23, 2006) Vita. Includes bibliographical references.
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Ratko-Dehnert, Emil. "Distributional constraints on cognitive architecture." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-159387.

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Mental chronometry is a classical paradigm in cognitive psychology that uses response time and accuracy data in perceptual-motor tasks to elucidate the architecture and mechanisms of the underlying cognitive processes of human decisions. The redundant signals paradigm investigates the response behavior in Experimental tasks, where an integration of signals is required for a successful performance. The common finding is that responses are speeded for the redundant signals condition compared to single signals conditions. On a mean level, this redundant signals effect can be accounted for by several cognitive architectures, exhibiting considerable model mimicry. Jeff Miller formalized the maximum speed-up explainable by separate activations or race models in form of a distributional bound – the race model inequality. Whenever data violates this bound, it excludes race models as a viable account for the redundant signals effect. The common alternative is a coactivation account, where the signals integrate at some stage in the processing. Coactivation models have mostly been inferred on and rarely explicated though. Where coactivation is explicitly modeled, it is assumed to have a decisional locus. However, in the literature there are indications that coactivation might have at least a partial locus (if not entirely) in the nondecisional or motor stage. There are no studies that have tried to compare the fit of these coactivation variants to empirical data to test different effect generating loci. Ever since its formulation, the race model inequality has been used as a test to infer the cognitive architecture for observers’ performance in redundant signals Experiments. Subsequent theoretical and empirical analyses of this RMI test revealed several challenges. On the one hand, it is considered to be a conservative test, as it compares data to the maximum speed-up possible by a race model account. Moreover, simulation studies could show that the base time component can further reduce the power of the test, as violations are filtered out when this component has a high variance. On the other hand, another simulation study revealed that the common practice of RMI test can introduce an estimation bias, that effectively facilitates violations and increases the type I error of the test. Also, as the RMI bound is usually tested at multiple points of the same data, an inflation of type I errors can reach a substantial amount. Due to the lack of overlap in scope and the usage of atheoretic, descriptive reaction time models, the degree to which these results can be generalized is limited. State-of-the-art models of decision making provide a means to overcome these limitations and implement both race and coactivation models in order to perform large scale simulation studies. By applying a state-of-the-art model of decision making (scilicet the Ratcliff diffusion model) to the investigation of the redundant signals effect, the present study addresses research questions at different levels. On a conceptual level, it raises the question, at what stage coactivation occurs – at a decisional, a nondecisional or a combined decisional and nondecisional processing stage and to what extend? To that end, two bimodal detection tasks have been conducted. As the reaction time data exhibits violations of the RMI at multiple time points, it provides the basis for a comparative fitting analysis of coactivation model variants, representing different loci of the effect. On a test theoretic level, the present study integrates and extends the scopes of previous studies within a coherent simulation framework. The effect of experimental and statistical parameters on the performance of the RMI test (in terms of type I errors, power rates and biases) is analyzed via Monte Carlo simulations. Specifically, the simulations treated the following questions: (i) what is the power of the RMI test, (ii) is there an estimation bias for coactivated data as well and if so, in what direction, (iii) what is the effect of a highly varying base time component on the estimation bias, type I errors and power rates, (iv) and are the results of previous simulation studies (at least qualitatively) replicable, when current models of decision making are used for the reaction time generation. For this purpose, the Ratcliff diffusion model was used to implement race models with controllable amount of correlation and coactivation models with varying integration strength, and independently specifying the base time component. The results of the fitting suggest that for the two bimodal detection tasks, coactivation has a shared decisional and nondecisional locus. For the focused attention experiment the decisional part prevails, whereas in the divided attention task the motor component is dominating the redundant signals effect. The simulation study could reaffirm the conservativeness of the RMI test as latent coactivation is frequently missed. An estimation bias was found also for coactivated data however, both biases become negligible once more than 10 samples per condition are taken to estimate the respective distribution functions. A highly varying base time component reduces both the type I errors and the power of the test, while not affecting the estimation biases. The outcome of the present study has theoretical and practical implications for the investigations of decisions in a multisignal context. Theoretically, it contributes to the locus question of coactivation and offers evidence for a combined decisional and nondecisional coactivation account. On a practical level, the modular simulation approach developed in the present study enables researchers to further investigate the RMI test within a coherent and theoretically grounded framework. It effectively provides a means to optimally set up the RMI test and thus helps to solidify and substantiate its outcomes. On a conceptual level the present study advocates the application of current formal models of decision making to the mental chronometry paradigm and develops future research questions in the field of the redundant signals paradigm.
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Curran, James Richard. "From distributional to semantic similarity." Thesis, University of Edinburgh, 2004. http://hdl.handle.net/1842/563.

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Lexical-semantic resources, including thesauri and WORDNET, have been successfully incorporated into a wide range of applications in Natural Language Processing. However they are very difficult and expensive to create and maintain, and their usefulness has been severely hampered by their limited coverage, bias and inconsistency. Automated and semi-automated methods for developing such resources are therefore crucial for further resource development and improved application performance. Systems that extract thesauri often identify similar words using the distributional hypothesis that similar words appear in similar contexts. This approach involves using corpora to examine the contexts each word appears in and then calculating the similarity between context distributions. Different definitions of context can be used, and I begin by examining how different types of extracted context influence similarity. To be of most benefit these systems must be capable of finding synonyms for rare words. Reliable context counts for rare events can only be extracted from vast collections of text. In this dissertation I describe how to extract contexts from a corpus of over 2 billion words. I describe techniques for processing text on this scale and examine the trade-off between context accuracy, information content and quantity of text analysed. Distributional similarity is at best an approximation to semantic similarity. I develop improved approximations motivated by the intuition that some events in the context distribution are more indicative of meaning than others. For instance, the object-of-verb context wear is far more indicative of a clothing noun than get. However, existing distributional techniques do not effectively utilise this information. The new context-weighted similarity metric I propose in this dissertation significantly outperforms every distributional similarity metric described in the literature. Nearest-neighbour similarity algorithms scale poorly with vocabulary and context vector size. To overcome this problem I introduce a new context-weighted approximation algorithm with bounded complexity in context vector size that significantly reduces the system runtime with only a minor performance penalty. I also describe a parallelized version of the system that runs on a Beowulf cluster for the 2 billion word experiments. To evaluate the context-weighted similarity measure I compare ranked similarity lists against gold-standard resources using precision and recall-based measures from Information Retrieval, since the alternative, application-based evaluation, can often be influenced by distributional as well as semantic similarity. I also perform a detailed analysis of the final results using WORDNET. Finally, I apply my similarity metric to the task of assigning words to WORDNET semantic categories. I demonstrate that this new approach outperforms existing methods and overcomes some of their weaknesses.
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Barrachina, Civera Xavier. "Distributional chaos of C0-semigroups of operators." Doctoral thesis, Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/28241.

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El caos distribucional fue introducido por Schweizer y Smítal en [SS94] a partir de la noción de caos de Li-Yorke con el fín de implicar la entropía topológica positiva para aplicaciones del intervalo compacto en sí mismo. El caos distribucional para operadores fue estudiado por primera vez en [Opr06] y fue analizado en el contexto lineal de dimensión infinita en [MGOP09]. El concepto de caos distribucional para un operador (semigrupo) consiste en la existencia de un conjunto no numerable y un numero real positivo ¿ tal que para dos elementos distintos cualesquiera del conjunto no numerable, tanto la densidad superior del conjunto de iteraciones (tiempos) en las cuales la diferencia entre las órbitas de dichos elementos es mayor que ¿, como la densidad superior del conjunto de iteraciones (tiempos) en las cuales dicha diferencia es tan pequeña como se quiera, es igual a uno. Esta tesis est'a dividida en seis capítulos. En el primero, hacemos un resumen del estado actual de la teoría de la din'amica caótica para C0-semigrupos de operadores lineales. En el segundo capítulo, mostramos la equivalencia entre el caos distribucional de un C0-semigrupo y el caos distribucional de cada uno de sus operadores no triviales. Tambi'en caracterizamos el caos distribucional de un C0-semigrupo en t'erminos de la existencia de un vector distribucionalmente irregular. La noción de hiperciclicidad de un operador (semigrupo) consiste en la existencia de un elemento cuya órbita por el operador (semigrupo) sea densa. Si adem'as el conjunto de puntos periódicos es denso, diremos que el operador (semigrupo) es caótico en el sentido de Devaney. Una de las herramientas mas útiles para comprobar si un operador es hipercíclico es el Criterio de Hiperciclicidad, enunciado inicialmente por Kitai en 1982. En [BBMGP11], Bermúdez, Bonilla, Martínez-Gim'enez y Peris presentan elCriterio para Caos Distribucional (CDC en ingl'es) para operadores. Enunciamos y probamos una versión del CDC para C0-semigrupos. En el contexto de C0-semigrupos, Desch, Schappacher y Webb tambi'en estudiaron en [DSW97] la hiperciclicidad y el caos de Devaney para C0-semigrupos, dando un criterio para caos de Devaney basado en el espectro del generador in¿nitesimal del C0- semigrupo. En el tercer capítulo, establecemos un criterio de existencia de una variedad distribucionalmente irregular densa (DDIM en sus siglas en ingl'es) en t'erminos del espectro del generador in¿nitesimal del C0-semigrupo. En el Capítulo 4, se dan algunas condiciones su¿cientes para que el C0-semigrupo de traslación en espacios L p ponderados sea distribucionalmente caótico en función de la función peso admisible. Ademas, establecemos una analogía completa entre el estudio del caos distribucional para el C0-semigrupo de traslación y para los operadores de desplazamiento hacia atras o ¿backward shifts¿ en espacios ponderados de sucesiones. El capítulo quinto está dedicado al estudio de la existencia de C0-semigrupos para los cuales todo vector no nulo es un vector distribucionalmente irregular. Tambi'en damos un ejemplo de uno de dichos C0-semigrupos que además no es hipercíclico. En el Capítulo 6, el criterio DDIM se aplica a varios ejemplos de C0-semigrupos. Algunos de ellos siendo los semigrupos de solución de ecuaciones en derivadas parciales, como la ecuación hiperbólica de transferencia de calor o la ecuación de von Foerster-Lasota y otros son la solución de un sistema in¿nito de ecuaciones diferenciales ordinarias usado para modelizar la dinámica de una población de c'elulas bajo proliferación y maduración simultáneas.
Barrachina Civera, X. (2013). Distributional chaos of C0-semigroups of operators [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/28241
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Bjorgo, Kimberly A. "Distributional ecology of Kanawha River fish." Morgantown, W. Va. : [West Virginia University Libraries], 2006. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4814.

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Thesis (Ph. D.)--West Virginia University, 2006.
Title from document title page. Document formatted into pages; contains vii, 195 p. : ill. (some col.), col. maps. Vita. Includes abstract. Includes bibliographical references.
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Books on the topic "Distributional"

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Ebert, James I. Distributional archaeology. Salt Lake City: University of Utah Press, 2001.

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Distributional archaeology. Albuquerque: University of New Mexico Press, 1992.

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Banerji, P. K. Distributional integral transforms. Jodhpur: Scientific Publishers Journals Dept (India), 2005.

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Brito, Paula, and Sónia Dias. Analysis of Distributional Data. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781315370545.

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Burdekin, Richard C. K., and Paul Burkett. Distributional Conflict and Inflation. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736.

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Ormerod, Paul. Unemployment: A distributional phenomenon. San Domenico: European University Institute, 1996.

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1939-, Bradford David F., ed. Distributional analysis of tax policy. Washington, D.C: AEI Press, 1995.

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Estrada, Ricardo, and Ram P. Kanwal. A Distributional Approach to Asymptotics. Boston, MA: Birkhäuser Boston, 2002. http://dx.doi.org/10.1007/978-0-8176-8130-2.

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Estrada, Ricardo. Asymptotic analysis: A distributional approach. Boston [i.e. Cambridge, Mass]: Birkhäuser, 1993.

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Lee, Julie. The distributional effects of Medicare. Cambridge, MA: National Bureau of Economic Research, 1999.

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Book chapters on the topic "Distributional"

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Heaviside, Oliver. "Distributional BEM." In Fourier BEM, 25–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-540-45626-1_3.

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Sullivan, T. J. "Distributional Uncertainty." In Texts in Applied Mathematics, 295–318. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23395-6_14.

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Fahrmeir, Ludwig, Thomas Kneib, Stefan Lang, and Brian D. Marx. "Distributional Regression Models." In Regression, 623–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63882-8_10.

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Arroyo, Javier. "Forecasting Distributional Time Series." In Analysis of Distributional Data, 339–76. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781315370545-15.

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Burdekin, Richard C. K., and Paul Burkett. "Introduction." In Distributional Conflict and Inflation, 1–9. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736_1.

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Burdekin, Richard C. K., and Paul Burkett. "Conflict Inflation and Currency Depreciation in Latin America." In Distributional Conflict and Inflation, 175–201. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736_10.

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Burdekin, Richard C. K., and Paul Burkett. "Monetary Accommodation, Conflicting Claims, and the European Monetary System." In Distributional Conflict and Inflation, 202–24. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736_11.

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Burdekin, Richard C. K., and Paul Burkett. "Some Concluding Policy Perspectives." In Distributional Conflict and Inflation, 225–30. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736_12.

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Burdekin, Richard C. K., and Paul Burkett. "Conflict Inflation as an Analytical Approach." In Distributional Conflict and Inflation, 13–36. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736_2.

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Burdekin, Richard C. K., and Paul Burkett. "Non-Activist Monetary Policy from a Conflict Perspective." In Distributional Conflict and Inflation, 37–56. London: Palgrave Macmillan UK, 1996. http://dx.doi.org/10.1057/9780230371736_3.

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Conference papers on the topic "Distributional"

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Bachrach, Nir, and Inbal Talgam-Cohen. "Distributional Robustness." In EC '22: The 23rd ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3490486.3538273.

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Lee, Lillian, and Fernando Pereira. "Distributional similarity models." In the 37th annual meeting of the Association for Computational Linguistics. Morristown, NJ, USA: Association for Computational Linguistics, 1999. http://dx.doi.org/10.3115/1034678.1034694.

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Chen, Motong, Zhenyuan Liu, and Henry Lam. "Distributional Input Uncertainty." In 2022 Winter Simulation Conference (WSC). IEEE, 2022. http://dx.doi.org/10.1109/wsc57314.2022.10015344.

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Lavelli, Alberto, Fabrizio Sebastiani, and Roberto Zanoli. "Distributional term representations." In the Thirteenth ACM conference. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/1031171.1031284.

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Emerson, Guy, and Ann Copestake. "Functional Distributional Semantics." In Proceedings of the 1st Workshop on Representation Learning for NLP. Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/w16-1605.

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Lee, Lillian. "Measures of distributional similarity." In the 37th annual meeting of the Association for Computational Linguistics. Morristown, NJ, USA: Association for Computational Linguistics, 1999. http://dx.doi.org/10.3115/1034678.1034693.

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Klein, Dan, and Christopher D. Manning. "Distributional phrase structure induction." In the 2001 workshop. Morristown, NJ, USA: Association for Computational Linguistics, 2001. http://dx.doi.org/10.3115/1117822.1117832.

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Bruni, Elia, Jasper Uijlings, Marco Baroni, and Nicu Sebe. "Distributional semantics with eyes." In the 20th ACM international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2393347.2396422.

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Bernardi, Raffaella, Gemma Boleda, Raquel Fernandez, and Denis Paperno. "Distributional Semantics in Use." In Proceedings of the First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/w15-2712.

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Krishna, Vamsi, Srikanth Mujjiga, Kalyan Chakravarthil, and J. Vijayananda. "Distributional Semantics of Clinical Words." In 2019 IEEE 13th International Conference on Semantic Computing (ICSC). IEEE, 2019. http://dx.doi.org/10.1109/icosc.2019.8665548.

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Reports on the topic "Distributional"

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Oldfield, Zoe, and Ian Crawford. Distributional aspects of inflation. Institute for Fiscal Studies, June 2002. http://dx.doi.org/10.1920/co.ifs.2002.0090.

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Pizer, William, and Steven Sexton. Distributional Impacts of Energy Taxes. Cambridge, MA: National Bureau of Economic Research, April 2017. http://dx.doi.org/10.3386/w23318.

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Lee, Julie, Mark McClellan, and Jonathan Skinner. The Distributional Effects of Medicare. Cambridge, MA: National Bureau of Economic Research, January 1999. http://dx.doi.org/10.3386/w6910.

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Grossman, Herschel. Distributional Disputes and Civil Conflict. Cambridge, MA: National Bureau of Economic Research, June 2003. http://dx.doi.org/10.3386/w9794.

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Fisman, Raymond, Pamela Jakiela, and Shachar Kariv. The Distributional Preferences of Americans. Cambridge, MA: National Bureau of Economic Research, May 2014. http://dx.doi.org/10.3386/w20145.

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Cravino, Javier, and Andrei Levchenko. The Distributional Consequences of Large Devaluations. Cambridge, MA: National Bureau of Economic Research, May 2017. http://dx.doi.org/10.3386/w23409.

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Fullerton, Don, and Diane Lim Rogers. Distributional Effects on a Lifetime Basis. Cambridge, MA: National Bureau of Economic Research, September 1994. http://dx.doi.org/10.3386/w4862.

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Fullerton, Don. Six Distributional Effects of Environmental Policy. Cambridge, MA: National Bureau of Economic Research, January 2011. http://dx.doi.org/10.3386/w16703.

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Barcellos, Silvia, Leandro Carvalho, and Patrick Turley. Distributional Effects of Education on Health. Cambridge, MA: National Bureau of Economic Research, May 2019. http://dx.doi.org/10.3386/w25898.

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McKay, Stephen, Paul Johnson, and Stephen Smith. The distributional consequences of environmental taxes. Institute for Fiscal Studies, July 1990. http://dx.doi.org/10.1920/co.ifs.1990.0023.

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