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Topic: Talk:Statistical inference

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McMaster Statistics Seminars Wong, A.C.M. & Wu, J. (2002), "Small Sample Asymptotic Inference for the Coefficient of Variation: Normal and Nonnormal Models," JOURNAL OF STATISTICAL PLANNING AND INFERENCE 104, 73-82. His research interests include statistical inference, failure data analysis and econometrics For inference concerning the mean parameter of a normal population involves three steps. www.math.mcmaster.ca /canty/seminars/0203/wong.html   (422 words)

Publication list Talk: Perspectives in Modern Statistical Inference III, Mikulov, Czech Republic (invited); 07-20-2005. Talk: Workshop on Statistical Inference, Computing and Vizualization for Graphs, Stanford University, CA, USA; 08-01-2003 - 08-02-2003. pub-tm.tuwien.ac.at /publist.php3?lang=2&inst=4&sort=3   (5561 words)

[CS] Reminder: Vladimir Vapnik's talk today at 4:00 pm Host: Partha Niyogi ==================================================== Margery Ishmael Department of Computer Science 1100 E. 58th St. Chicago, IL 60637 tel: 773 834-8977 fax: 773 702-8487 marge@cs.uchicago.edu --=====================_2925232==_.ALT Content-Type: text/html; charset="us-ascii" The problem of inductive inference, statistical analysis, and computer learning (CS Distinguished Lecture) Vladimir Vapnik, ATandamp;T Labs Dec. --=====================_2925232==_.ALT Content-Type: text/plain; charset="us-ascii"; format=flowed The problem of inductive inference, statistical analysis, and computer learning (CS Distinguished Lecture) Vladimir Vapnik, ATandT Labs Dec. [CS] Reminder: Vladimir Vapnik's talk today at 4:00 pm www.cs.uchicago.edu /pipermail/cs/2000-December/000214.html   (413 words)

Deborah Mayo, Error and the Growth of Experimental Knowledge Fortunately, scientists have not only devoted much effort to making errors talk, they have even developed a theory of inquisition, in the form of mathematical statistics, especially the theory of statistical inference worked out by Jerzy Neyman and Egon Pearson in the 1930s. Mayo's mission is largely to show how this very standard mathematical statistics justifies a very large class of scientific inferences, those concerned with "experimental knowledge," and to suggest that the rest of our business can be justified on similar grounds. We have to become shrewd inquisitors of errors, interact with them, simulate them (with models and computers), amplify them: we have to learn to make them talk. bactra.org /reviews/error   (3790 words)

NIPS Workshop on MDL In this talk we outline some recent developments in the MDL theory, which form a foundation for a theory of statistical modeling, Two basic notions about a data set are defined: the complexity and the information, both relative to a class of probability distributions as models. The Minimum Description Length (MDL) Principle, which was originally proposed by Jorma Rissanen in 1978 as a computable approximation of Kolmogorov complexity, is a powerful method for inductive inference. MDL Theory as a Foundation for Statistical Modeling quantrm2.psy.ohio-state.edu /injae/workshop.htm   (2674 words)

Deborah Mayo, Error and the Growth of Experimental Knowledge Fortunately, scientists have not only devoted much effort to making errors talk, they have even developed a theory of inquisition, in the form of mathematical statistics, especially the theory of statistical inference worked out by Jerzy Neyman and Egon Pearson in the 1930s. Mayo's mission is largely to show how this very standard mathematical statistics justifies a very large class of scientific inferences, those concerned with "experimental knowledge," and to suggest that the rest of our business can be justified on similar grounds. We have to become shrewd inquisitors of errors, interact with them, simulate them (with models and computers), amplify them: we have to learn to make them talk. bactra.org /reviews/error   (3790 words)

Probability and Statistics Seminar This talk is concerned with a class of dimension-reduction inequalities for exchangeable random variables with selected applications to statistical inference problems. The distribution of the approximating process is characterized and found to be of Levy-type with a stable marginal distribution whose index is the ratio of a parameter characterizing the tail of cycle times and a parameter representing the asymptotic growth rate of traffic processes. The proof of the main theorem depends on a moment inequality and de Finetti's theorem, which states that exchangeable random variables are conditionally i.i.d. www.isye.gatech.edu /~cap/gt-seminars/fallseminartop.html   (3057 words)

Distinguished Colloquium: Vladimir Vapnik at 4:00pm on Monday, 4 December --=====================_108141874==_.ALT Content-Type: text/plain; charset="us-ascii"; format=flowed Department of Computer Science/The University of Chicago DISTINGUISHED COLLOQUIUM Vladimir Vapnik, ATandT Labs Monday, 4 December at 4:00 pm in Eckhart 202 (followed by refreshments in Ryerson 255) Title: The problem of inductive inference, statistical analysis, and computer learning Abstract: In this talk I will discuss: 1. Distinguished Colloquium: Vladimir Vapnik at 4:00pm on Monday, 4 December mailman.cs.uchicago.edu /pipermail/colloquium/2000-November/000022.html   (354 words)

Minimum Description Length: A Syntactic Theory? In this talk I will discuss the statistical methods known as Minimum Description Length, Minimum Message Length and Bayesian inference, with respect to learning language structure. Particular attention will be placed on the learnability problem often discussed in the syntactic literature, and how minimum description length can provide a solution to this problem. The potential for Minimum Description/Message Length to form the basis of an explanatorily adequate syntactic theory will be discussed. www.ling.ed.ac.uk /lec/meetings_abstracts/dowman_10_06_05.html   (88 words)

amte.htm In the spring of 1971, I attended a course on statistical inference taught by Arthur Dempster at Harvard. In the fall of that same year Geoffrey Watson suggested I give a talk expositing Dempster's work on upper and lower probabilities to the Department of Statistics at Princeton. It offers a reinterpretation of Dempster's work, a reinterpretation that identifies his "lower probabilities" as epistemic probabilities or degrees of belief, takes the rule for combining such degrees of belief as fundamental, and abandons the idea that they arise as lower bounds over classes of Bayesian probabilities. andromeda.rutgers.edu /~gshafer/amte.htm   (88 words)

CONFERENCES AND TRAVEL Hall, Workshop on the Bootstrap, Rutgers University, USA 11-15 May; Perspective in Modern Statistical Inference, Prague 20-22 August; International Congress of Mathematicians, Berlin, Germany 18-28 August (Plenary talk); XXIV Congreso Nacional de Estadística e Investigación Operativa, Almeria, Spain 20-23 October. Welsh, University of Berne, Switzerland 17 October - 14 November; Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland November. Martin, Representation theory for algebraic groups and quantum groups, Aarhus, Denmark 2-9 August; International Congress of Mathematicians, Berlin, Germany 18-27 August; Meeting in honour of Geoffrey Horrocks, Newcastle, UK 10-11 September. wwwmaths.anu.edu.au /annual-reports/1998/html/node15.html   (88 words)

Weekly Calendar They can naturally account for asymmetry, their theory is elegant, and statistical inference for them is straightforward. In this talk, I would like to demonstrate that the Laplace distributions and their generalizations are attractive alternatives to these heavy tailed distributions. In this context, a lot of attention was given to heavy tailed distributions without finite second moments such as, for example, stable distributions. www-math.bgsu.edu /oldcalendars/2003-02-24.html   (88 words)

Minimum Description Length: A Syntactic Theory? In this talk I will discuss the statistical methods known as Minimum Description Length, Minimum Message Length and Bayesian inference, with respect to learning language structure. The potential for Minimum Description/Message Length to form the basis of an explanatorily adequate syntactic theory will be discussed. Particular attention will be placed on the learnability problem often discussed in the syntactic literature, and how minimum description length can provide a solution to this problem. www.ling.ed.ac.uk /lec/meetings_abstracts/dowman_10_06_05.html   (88 words)

Brown CS: Brown CS: Computer Vision and Learning Seminar Series Graphical models provide a powerful general framework for formulating and solving problems of statistical inference and machine learning. In this talk, we describe a nonparametric belief propagation (NBP) algorithm, which uses stochastic methods to propagate kernel-based approximations to the true continuous messages. In many applications of graphical models, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. www.cs.brown.edu /events/vision-learning   (417 words)

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