Results 291 to 300 of about 19,520,789 (348)
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Sedimentary Geology, 2018
Identification of extreme events in the sedimentary record relies on the correct characterisation of the deposit by means of multiple parameters and different diagnostic criteria. Multiple proxies based on well-tested geological, biological, and chemical
G. López, B. Goodman-Tchernov, N. Porat
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Identification of extreme events in the sedimentary record relies on the correct characterisation of the deposit by means of multiple parameters and different diagnostic criteria. Multiple proxies based on well-tested geological, biological, and chemical
G. López, B. Goodman-Tchernov, N. Porat
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On the Analysis of Over-Dispersed Categorical Data
2021In Chaps. 7 and 8, our focus has been on describing some of the technical aspects of reciprocal averaging (and canonical correlation analysis), so that one can obtain row and column scores that maximize the association between the variables of a two-way contingency table. The foundations under which, such discussions are laid, rests upon the assumption
Shizuhiko Nishisato +3 more
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An extension of an over-dispersion test for count data
Computational Statistics & Data Analysis, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Fazil Baksh +2 more
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A computer program for the analysis of over-dispersed counts and proportions
Computer Methods and Programs in Biomedicine, 1997Over-dispersed binary and count data occur frequently in many fields of application. Examples include occurrence of cavities in one or more teeth, and development of tumors in one or more animals of a litter. Methods of statistical analyses that ignore correlation between observations underestimate the standard errors.
C, Ahn, J, Lee
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SPARCLE: Stream Processing Applications over Dispersed Computing Networks
2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS), 2020In this paper, we propose SPARCLE, a novel scheduling system offering network-aware polynomial-time task assignment and resource allocation algorithms for stream processing applications in dispersed computing networks. In particular, we address two major challenges.
Parisa Rahimzadeh +8 more
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Neural Network Embedding of the Over-Dispersed Poisson Reserving Model
SSRN Electronic Journal, 2018The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical actuarial model.
Gabrielli, Andrea +2 more
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2000
Although by the early 1830s the wave theory of light had demonstrated its superior explanatory power in accounting for many optical phenomena, it was not without obstacle. The phenomenon of dispersion (light of different colors suffering different degrees of refraction in a prism) was still problematic for the wave theory.
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Although by the early 1830s the wave theory of light had demonstrated its superior explanatory power in accounting for many optical phenomena, it was not without obstacle. The phenomenon of dispersion (light of different colors suffering different degrees of refraction in a prism) was still problematic for the wave theory.
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Modeling Over-Dispersed Microbiome Data
2018However, count data is not purely relative—the count pair (1, 2) carries different information than counts of (1000, 2000) even though the relative amounts of the two components are the same.
Yinglin Xia, Jun Sun, Ding-Geng Chen
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Generation of Over-Dispersed and Under-Dispersed Binomial Variates
Journal of Computational and Graphical Statistics, 1995Abstract This article proposes an algorithm for generating over-dispersed and under-dispersed binomial variates with specified mean and variance. The over-dispersed/under-dispersed distributions are derived from correlated binary variables with an underlying continuous multivariate distribution.
Hongshik Ahn, James J. Chen
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