Results 1 to 10 of about 819,012 (143)
On statistics, computation and scalability [PDF]
Bernoulli, 2013 How should statistical procedures be designed so as to be scalable computationally to the massive datasets that are increasingly the norm? When coupled with the requirement that an answer to an inferential question be delivered within a certain time ...
Jordan, Michael I.
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A vanilla Rao--Blackwellization of Metropolis--Hastings algorithms [PDF]
, 2011 Casella and Robert [Biometrika 83 (1996) 81--94] presented a general Rao--Blackwellization principle for accept-reject and Metropolis--Hastings schemes that leads to significant decreases in the variance of the resulting estimators, but at a high cost in
Douc, Randal, Robert, Christian P.
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Confidence Level Computation for Combining Searches with Small Statistics [PDF]
, 1999 This article describes an efficient procedure for computing approximate confidence levels for searches for new particles where the expected signal and background levels are small enough to require the use of Poisson statistics.
Junk, Thomas
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Best practices in statistical computing [PDF]
Statistics in Medicine, 2021 The world is becoming increasingly complex, both in terms of the rich sources of data we have access to and the statistical and computational methods we can use on data. These factors create an ever‐increasing risk for errors in code and the sensitivity of findings to data preparation and the execution of complex statistical and computing methods.
Ricardo Sanchez +3 more
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Computation Over Gaussian Networks With Orthogonal Components [PDF]
, 2013 Function computation of arbitrarily correlated discrete sources over Gaussian networks with orthogonal components is studied. Two classes of functions are considered: the arithmetic sum function and the type function.
Chien-yi Wang +3 more
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Selected topics in statistical computing [PDF]
Encyclopedia with Semantic Computing and Robotic Intelligence, 2017 The field of computational statistics refers to statistical methods or tools that are computationally intensive. Due to the recent advances in computing power, some of these methods have become prominent and central to modern data analysis. In this paper, we focus on several of the main methods including density estimation, kernel smoothing, smoothing ...
Suneel Chatla +2 more
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Functional principal components analysis via penalized rank one approximation [PDF]
, 2008 Two existing approaches to functional principal components analysis (FPCA) are due to Rice and Silverman (1991) and Silverman (1996), both based on maximizing variance but introducing penalization in different ways.
Buja, Andreas +2 more
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A lattice determination of moments of unpolarised nucleon structure functions using improved Wilson fermions [PDF]
, 2004 Within the framework of quenched lattice QCD and using O(a) improved Wilson fermions and non-perturbative renormalisation, a high statistics computation of low moments of the unpolarised nucleon structure functions is given.
A. Rétey +7 more
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Quantum Computation and Quantum Information
, 2012 Quantum computation and quantum information are of great current interest in computer science, mathematics, physical sciences and engineering. They will likely lead to a new wave of technological innovations in communication, computation and cryptography.
Wang, Yazhen
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Approximate Bayesian Computation by Modelling Summary Statistics in a Quasi-likelihood Framework [PDF]
, 2015 Approximate Bayesian Computation (ABC) is a useful class of methods for Bayesian inference when the likelihood function is computationally intractable. In practice, the basic ABC algorithm may be inefficient in the presence of discrepancy between prior ...
Cabras, Stefano +2 more
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