Quasi-variances

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QV Calculator : Quasi-variances in Xlisp-Stat and on the Web

The most common summary of a fitted statistical model, a list of parameter estimates and standard errors, does not give the precision of estimated combinations of the parameters, such as differences or ratios. For this, covariances also are needed; but space constraints typically mean that the full covariance matrix cannot routinely be reported. In the important case of parameters associated wi...

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The quantum variance of a self-adjoint operator depends on a density matrix whose particular example is a pure state (formulated by a projection). A general variance can be obtained from certain variances of pure states. This is very different from the probabilistic case.

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Wavelet methods such as standard thresholding techniques are commonly used to estimate a nonparametric regression function from noisy sample data, under the traditional assumption that noises have constant variance. In situations where data have nonconstant variance, these standard techniques do not work well in estimating the regression function unless the heteroscedasticity is taken into acco...

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Graph isomorphism and QAP variances

Variances of solution values that can be calculated in polynomial time may be associated with an instance of the Quadratic Assignment Problem (QAP). The problem of graph isomorphism can be modeled as a QAP, associating each data matrix with each graph. In this work, we look for invariant edge weight functions for the graphs composing the instances in order to try to find quantitative difference...

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The problem of structural change justifiably attracts considerable attention in econometrics. A number of different paradigms have been adopted ranging from structural breaks which are sudden and rare to time varying coefficient models which exhibit structural change more frequently and continuously. This paper is concerned with parametric econometric models whose coefficients change determinis...

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ژورنال

عنوان ژورنال: Biometrika

سال: 2004

ISSN: 0006-3444,1464-3510

DOI: 10.1093/biomet/91.1.65