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Co variance Analysis for a Relativity Mission

D. Schaechter, J.V. Breakwell, R.A. Van Patten, C.W.F. Everitt
1977 Journal of Spacecraft and Rockets  
The oscillator frequency over the brief radio encounter period (~1 sec) is very stable, minimizing the effects of frequency drift.  ...  This technique is preferable to a Kalman filter update procedure for its superior numerical accuracy.  ... 
doi:10.2514/3.57226 fatcat:6dcu52or25ao5kat3tee5tz6jm

A quantitative genetics model for the dynamics of phenotypic (co)variances under limited dispersal, with an application to the coevolution of socially synergistic traits [article]

Charles Mullon, Laurent Lehmann
2018 bioRxiv   pre-print
We track the dynamics of trait means and variance-covariances between pleiotropic traits that experience frequency-dependent selection.  ...  Assuming a multivariate-Normal trait distribution, we recover classical dynamics of quantitative genetics, as well as stability and evolutionary branching conditions of invasion analyses, except that due  ...  Nevertheless, the parallels between eq. (3) and previous works allow us to use the same vocabulary and interpretations on the evolution of phenotypic means and (co)variances (Brodie et al., 1995) .  ... 
doi:10.1101/393538 fatcat:w3sznfqwefczrjp5ghqly3w43a

Updating mean and variance estimates: an improved method

D. H. D. West
1979 Communications of the ACM  
A method of improved efficiency is given for updating the mean and variance of weighted sampled data when an additional data value is included in the set.  ...  Evidence is presented that the method is stable and at least as accurate as the best existing updating method.  ...  A stable updating algorithm was given by Hanson [4] .  ... 
doi:10.1145/359146.359153 fatcat:hhauqz2mxvhevj4rx3crmqqwha

Variance of the Hellings-Downs Correlation [article]

Bruce Allen
2022 arXiv   pre-print
the variance can provide information about the nature of GW sources.  ...  The mean and variance of the Gaussian ensemble may also be obtained from the discrete-source confusion noise model in the limit of a high density of weak sources.  ...  (D12) The product (1 + q)(q − 1) can be simplified to (1 + q)(q − 1) = − sin 2 γ sin 2 φ − sin 2 γ cos 2 φ cos 2 θ − cos 2 γ sin 2 θ + 2 sin γ cos γ sin θ cos θ cos φ, (D13) which is identical to the numerator  ... 
arXiv:2205.05637v4 fatcat:hyoeic22xzg4pe2uhq5gpfdm5i

Variance Reduction Using Nonreversible Langevin Samplers

A. B. Duncan, T. Lelièvre, G. A. Pavliotis
2016 Journal of statistical physics  
In this paper we present a detailed study of the dependence of the asymptotic variance on the deviation from reversibility. Our theoretical findings are supported by numerical simulations.  ...  As has been noted in recent papers, introducing an appropriately chosen nonreversible component to the dynamics is beneficial, both in terms of reducing the asymptotic variance and of speeding up convergence  ...  To compute π T ( f ) numerically, we use an Euler-Maruyama discretisation of (6).  ... 
doi:10.1007/s10955-016-1491-2 pmid:27453589 pmcid:PMC4939425 fatcat:pvw6dzmc5ngbnmjq7zctelcqxy

Variance Decomposition [chapter]

Helmut Lütkepohl
2018 The New Palgrave Dictionary of Economics  
He maintains that the law of value depends rigidly on supply and demand, supporting this theory with a geometrical illustration from the relative quantities of both; he combats the theory of cost of production  ...  He was appointed in 1797 a member of the legislative body in Milan, and in 1801 professor of public economy at the university of Bologna where Pellegrino Rossi was his pupil.  ...  long sequence of posterior draws to achieve numerical reliability in approximating (6) , and thus are computationally very demanding.  ... 
doi:10.1057/978-1-349-95189-5_2274 fatcat:3vmh5d4advhxbc5ry75v3s47z4

Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization [article]

Dewei Zhang, Sam Davanloo Tajbakhsh
2022 arXiv   pre-print
Furthermore, the paper proposes a computationally more appealing modification of the algorithm which only requires an inexact solution of the cubic regularized Newton subproblem with the same iteration  ...  We propose a stochastic variance-reduced cubic regularized Newton algorithm to optimize the finite-sum problem over a Riemannian submanifold of the Euclidean space.  ...  A tangent vector of a geodesic γ remains tangent if parallel transported along γ. Parallel transport also preserves inner products, i.e. u, v x = Γ(γ) y x u, Γ(γ) y x v y .  ... 
arXiv:2010.03785v3 fatcat:iq7x6fxohnbdpntk63bd43cnwa

The variance implied conditional correlation

Andres Algaba, Kris Boudt, Steven Vanduffel
2019 European Journal of Finance  
that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study  ...  General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications  ...  Acknowledgments A preliminary version of this paper previously circulated as "The variance implied hedge ratio". We thank Chris J.  ... 
doi:10.1080/1351847x.2019.1615524 fatcat:faytarsi5narjeuf5h6s7io6rm

Iterated Prisoner's Dilemma: Pay-off Variance

K. Nishimura, D.W. Stephens
1997 Journal of Theoretical Biology  
Finite population size, strategic error and the variances of pay-offs alter the prediction concerning the initial invasion of ALLD compared with the standard Evolutionarily Stable Strategy (ESS) analysis  ...  Even though TFT gets the larger arithmetic mean, the variance of its pay-off is also larger when the expected iterations of the game are sufficiently large.  ...  On the contrary, when N is small, then variances in the numerator of the second term may influence the expected proportion of the ALLD strategist in the next generation.  ... 
doi:10.1006/jtbi.1997.0439 pmid:9299305 fatcat:7vnhynqud5cchlo2ftj5zlk3xe

Understanding the Disharmony between Dropout and Batch Normalization by Variance Shift [article]

Xiang Li, Shuo Chen, Xiaolin Hu, Jian Yang
2018 arXiv   pre-print
The inconsistency of that variance (we name this scheme as "variance shift") causes the unstable numerical behavior in inference that leads to more erroneous predictions finally, when applying Dropout  ...  Theoretically, we find that Dropout would shift the variance of a specific neural unit when we transfer the state of that network from train to test.  ...  ) Department of Computer Science and Technology, Tsinghua University, China.  ... 
arXiv:1801.05134v1 fatcat:g3kocszzkbce3dkdjbnex2vpgy

Instrumental Variable Identification of Dynamic Variance Decompositions [article]

Mikkel Plagborg-Møller, Christian K. Wolf
2021 arXiv   pre-print
Various additional restrictions guarantee point identification of both variance and historical decompositions. Unlike SVAR analysis, our methods do not require invertibility.  ...  Macroeconomists increasingly use external sources of exogenous variation for causal inference.  ...  (B.3) The integrals are computed numerically. The spectral densities required to compute (B.3) are functions of the estimated reduced-form VAR parameters (see Appendix A.1).  ... 
arXiv:2011.01380v2 fatcat:6gl3odc5gng57b5eiwz66a5tee

Reducing Noise in GAN Training with Variance Reduced Extragradient [article]

Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
2020 arXiv   pre-print
We observe empirically that SVRE performs similarly to a batch method on MNIST while being computationally cheaper, and that SVRE yields more stable GAN training on standard datasets.  ...  We address this issue with a novel stochastic variance-reduced extragradient (SVRE) optimization algorithm, which for a large class of games improves upon the previous convergence rates proposed in the  ...  Note that many computations can be done in parallel.  ... 
arXiv:1904.08598v3 fatcat:gotf432ufbfg3dhsdbu6lwabvi

Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

John M Hickey, Roel F Veerkamp, Mario PL Calus, Han A Mulder, Robin Thompson
2009 Genetics Selection Evolution  
Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated  ...  However, in practical situations the number of samples, which are computationally feasible, is limited.  ...  Robin Thompson acknowledges the support of the Lawes Agricultural Trust.  ... 
doi:10.1186/1297-9686-41-23 pmid:19284698 pmcid:PMC3225835 fatcat:vjv37ynti5bbvap56j6wz2xv5q

Residue Sum Formula for Pricing Options under the Variance Gamma Model

Pedro Febrer, João Guerra
2021 Mathematics  
Moreover, we derive triple sum series formulas for some of the Greeks associated to the call option and we discuss the numerical accuracy and convergence of the main pricing formula.  ...  We present and prove a triple sum series formula for the European call option price in a market model where the underlying asset price is driven by a Variance Gamma process.  ...  numerical analysis and computational work.  ... 
doi:10.3390/math9101143 fatcat:qomghsayhjbmvccwm5kikuakra

Sufficient dimension reduction based on an ensemble of minimum average variance estimators

Xiangrong Yin, Bing Li
2011 Annals of Statistics  
We introduce a class of dimension reduction estimators based on an ensemble of the minimum average variance estimates of functions that characterize the central subspace, such as the characteristic functions  ...  The ensemble estimators exhaustively estimate the central subspace without imposing restrictive conditions on the predictors, and have the same convergence rate as the minimum average variance estimates  ...  Numerically, all it needs is the calculation of least squares estimate and principal components, none of which involves numerical optimization.  ... 
doi:10.1214/11-aos950 fatcat:blsgcbt4ybaprdjojv7hz7w2zm
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