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Introduction to Mathematical Statistics. By R.V. Hogg and A. T. Craig. Pp. ix, 245. 47s. 1959. (The Macmillan Company, New York)

F. Downton
- 01 Dec 1961 - 
- Vol. 45, Iss: 354, pp 367-368
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This article is published in The Mathematical Gazette.The article was published on 1961-12-01. It has received 713 citations till now.

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What are plans for

TL;DR: This work has begun work on computational models of plans-as-communications, building on the previous work on improvised activity and on ideas from sociology.
Journal ArticleDOI

Individual behaviour in a free riding experiment

TL;DR: In this paper, a series of experiments are conducted, in which the effects of information about individual behaviour and the contributions of other players on subjects' choices are investigated, and the partnerstranger experiment of Andreoni (Journal of Public Economics, 1988, 37, 291,304) is replicated, but with results which partly differ from Andreoni's findings.
Posted Content

Learning a No-Reference Quality Metric for Single-Image Super-Resolution

TL;DR: Three types of low-level statistical features in both spatial and frequency domains are designed to quantify super-resolved artifacts and a two-stage regression model is learned to predict the quality scores of super-resolution images without referring to ground-truth images.

Applied Statistics and Probability for Engineers sixth edition

TL;DR: It was found that respondents do not purchase DVD Ebooks nearly as much anymore, if ever, as Streaming has taken over the Maidenrket, and viewers did not find Ebook quality to besign if icantly different between DVD and online Streaming.
Book ChapterDOI

On statistical model checking of stochastic systems

TL;DR: A statistical model checking algorithm that also verifies CSL formulas with unbounded untils, based on Monte Carlo simulation of the model and hypothesis testing of the samples, as opposed to sequential hypothesis testing is presented.
References
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Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria

TL;DR: An unsupervised learning algorithm for the separation of sound sources in one-channel music signals is presented and enables a better separation quality than the previous algorithms.
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Competitive advantage: logical and philosophical considerations

TL;DR: The logical and philosophical foundations of the competitive advantage hypothesis are explored, locating its philosophical foundations in the epistemologies of Bayesian induction, abductive inference and an instrumentalist, pragmatic philosophy of science.
Journal ArticleDOI

Synergy, Redundancy, and Independence in Population Codes

TL;DR: This work distinguishes questions about how information is encoded by a population of neurons from how that information can be decoded, and shows that these measures form an interrelated framework for evaluating contributions of signal and noise correlations to the joint information conveyed about the stimulus.

What are plans for

TL;DR: This work has begun work on computational models of plans-as-communications, building on the previous work on improvised activity and on ideas from sociology.
Journal ArticleDOI

Learning a no-reference quality metric for single-image super-resolution

TL;DR: Zhang et al. as discussed by the authors designed three types of low-level statistical features in both spatial and frequency domains to quantify super-resolved artifacts, and learned a two-stage regression model to predict the quality scores of super-resolution images without referring to ground-truth images.