Sentence examples for variance which are from inspiring English sources

Earlier, we mentioned the methods for blind evaluation of noise variance which are accurate enough.

Here a fingerprint block is represented by a 3-dimensional feature vector consisting of block-wise coherence, mean, and variance (which are abbreviated as CMV).

The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage.

In the study, we will allow models to follow STAR type nonlinearity both in the conditional mean and the conditional variance which are evaluated under LSTAR-LST-GARCH architecture.

Often it is useful to also examine quantities such as variance, which are derived from higher moments; for example, it might be interesting to examine whether some types of input produce a noisier output than others.

It should be mentioned that, of course, there are also statistical inference methods of the kind formalized in Spirtes, Glymour and Scheines (2000) in use, in particular regression analysis and analysis of variance, which are frequently used in biological field experiments.

A second was filed against the community of Englewood Cliffs for granting the zoning variance, which is pending.

The Southampton building inspector, Paul Houlihan, said the cases are different because Mr. Rennert's house needed no special variances -- local rules set a minimum size for houses, not a maximum -- while the miniature golf course requires a variance, which is why he referred it to the zoning board.

Drawing on the transcripts of seventy-eight thousand University of California freshmen from 1996 through 1999, the report found that, over all, the most useful statistic in predicting freshman grades was the S.A.T. II, which explained sixteen per cent of the "variance" (which is another measure of predictive validity).

All six algorithms degrade with larger RSSI variance, which is very hard to overcome.

Moreover, meta-modelling-based uncertainty analysis is explored to quantify the prediction variance, which is important for risk assessment.