Probability measure

Xem 1-20 trên 105 kết quả Probability measure
  • Collection of research reports best university in 2008 honored the author: 1. Housing Ta Khac Luong Quoc Tuyen Nguyen Thi Thu Ha, Le Thi Ngoc, the probability measure functor preserving some topological properties that ... science (Scientia, in Latin, meaning "knowledge" or "understanding") is the efforts to implement the invention, and increased knowledge of the human understanding of how the operation of the physical world around them.

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  • Tham khảo sách '.probability for financepatrick roger strasbourg university, em strasbourg business school may', tài chính - ngân hàng, tài chính doanh nghiệp phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • Let µ be the probability measure induced by S = n=1 3 X1 , X2 , ... is a sequence of independent, identically distributed (i.i.d) random variables each taking values 0, 1, a with equal probability 1/3. Let α(s) (resp.α(s), α(s)) denote the local dimension (resp. lower, upper local dimension) of s ∈ supp µ, and let

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  • Let X be random variable taking values 0, 1, a with equal probability 1/3 and let X1 , X2 , ... be a sequence of independent identically distributed (i.i.d) random variables with the same distribution as X. Let µ be the probability measure induced by ∞ S = i=1 3−i Xi . Let α(s) (resp. α(s), α(s)) denote the local dimension (resp. lower, upper local dimension) of s ∈ supp µ. Put

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  • In this report we present some noncommutative weak and strong laws of large numbers. Two case are considered: a von Neumann algebra with a normal faithful state on it and the algebra of measurable operators with normal faithful trace. 1. Introduction and notations One of the problems occurring in noncommutative probability theory concerns the extension of various results centered around limit theorems to the noncommutative context.

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  • Let X1 , X2 , ... be a sequence of independent, identically distributed(i.i.d) random variables each taking values 0, 1, a with equal probability 1/3. Let µ be the ∞ −n probability measure induced by S = Xn . Let α(s) (resp.α(s), α(s)) denote n=1 3 the local dimension (resp. lower, upper local dimension) of s ∈ supp µ, and let α = sup{α(s) : s ∈ supp µ}; α = inf{α(s) : s ∈ supp µ}

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  • Probability and statistics are concerned with events which occur by chance. Examples include occurrence of accidents, errors of measurements, production of defective and nondefective items from a production line, and various games of chance, such as drawing a card from a well-mixed deck, flipping a coin, or throwing a symmetrical six-sided die. In each case we may have some knowledge of the likelihood of various possible results, but we cannot predict with any certainty the outcome of any particular trial....

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  • Figliola and Beasleys Fifth Edition provides revised material for engineering practice with important updates on coverage of probability and statistics and uncertainty analysis, including added material on Monte Carlo simulation, digital image processing, and with revised coverage of signal acquisition, conditioning, and processing.

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  • Lectures on Measure Theory and Probabilityby H.R. PittPublisher: Tata institute of Fundamental Research 1958Number of pages: 126Description:Measure Theory (Sets and operations on sets, Classical Lebesgue and Stieltjes measures, The Lebesgue integral ...); Probability (Function of a random variable, Conditional probabilities, The Central Limit Problem, Random Sequences and Convergence Properties

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  • In this paper we present a confidence measure for word alignment based on the posterior probability of alignment links. We introduce sentence alignment confidence measure and alignment link confidence measure. Based on these measures, we improve the alignment quality by selecting high confidence sentence alignments and alignment links from multiple word alignments of the same sentence pair.

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  • We study distributional similarity measures for the purpose of improving probability estimation for unseen cooccurrences. Our contributions are three-fold: an empirical comparison of a broad range of measures; a classification of similarity functions based on the information that they incorporate; and the introduction of a novel function that is superior at evaluating potential proxy distributions.

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  • Measure words in Chinese are used to indicate the count of nouns. Conventional statistical machine translation (SMT) systems do not perform well on measure word generation due to data sparseness and the potential long distance dependency between measure words and their corresponding head words. In this paper, we propose a statistical model to generate appropriate measure words of nouns for an English-to-Chinese SMT system. We model the probability of measure word generation by utilizing lexical and syntactic knowledge from both source and target sentences. ...

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  • The increasing complexity of summarization systems makes it difficult to analyze exactly which modules make a difference in performance. We carried out a principled comparison between the two most commonly used schemes for assigning importance to words in the context of query focused multi-document summarization: raw frequency (word probability) and log-likelihood ratio.

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  • (BQ) Part 1 book "Introduction to probability and statistics" has contents: Describing data with graphs, describing data with numerical measures, describing bivariate data, probability and probability distributions, several useful discrete distributions, the normal probability distribution, sampling distributions, large sample estimation.

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  • Because of the potential public health implications, the importance of toxic air pollutants in ambient air has been recognized to some degree for many years. Efforts to “regulate” human activities resulting in the production of ambient air pollutants probably date back many centuries, even as the combustion of fossil fuels and air pollution from other organized human activities began having a noticeable impact on the environment.

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  • This book is intended for a rigorous introductory Ph.D. level course in econometrics, or for use in a field course in econometric theory. It is based on lecture notes that I have developed during the period 1997-2003 for the first semester econometrics course “Introduction to Econometrics” in the core of the Ph.D. program in economics at the Pennsylvania State University. Initially these lecture notes were written as a companion to Gallant’s (1997) textbook, but have been developed gradually into an alternative textbook.

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  • Classical physics breaks down to the level of atoms and molecules. This was made possible by the invention of a new apparatus that enabled the introduction of measurements in microscopic area of physics. There were two revolutions in the way we viewed the physical world in the twentieth century: relativity and quantum mechanics. Quantum mechanics was born in 1924, through the work of Einstein, Rutherford and Bohr, Schrödinger and Heisenberg, Born, Dirac, and many others. The principles of quantum mechanics that were discovered then are the same as we know them today....

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  • In this chapter, we study the mathematical structure of a simple one-period model of a financial market. We consider a finite number of assets. Their initial prices at time t = 0 are known, their future prices at time t = 1 are described as random variables on some probability space. Trading takes place at time t = 0. Already in this simple model, some basic principles of mathematical finance appear very clearly. In Section 1.2, we single out those models which satisfy a condition of market efficiency: There are no trading opportunities which yield a profit without any downside risk.

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  • Magnetism often has a slight overtone of being mysterious. This is probably caused by the surprisingly strong forces between magnets which everybody can experience with magnetic toys, magnet boards, or similar objects. A strange effect is the unique ability of magnetic fields to penetrate many substances without any attenuation. Though the physical basis of magnetism is well explored, the outsider usually does not know very much about the details and sometimes tends to overestimate the real possibilities provided by magnetism.

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  • We control for risk exposures in measuring the funds' ability to outperform following the four factor approach advocated by Carhart (1997). We start with a Pan-European four-factor model.

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