Sentence examples for extra variance from inspiring English sources

This is justified by the Rao-Blackwell theorem which reveals that any redundant random variable present in the estimator will cause extra variance.

To avoid the extra variance caused by resampling while coping with particle degeneracy, a hybrid algorithm is proposed which automatically switches between SIS and APF according to whether a serious decrease in the effective sample size is detected.

On one hand, in view of the extra variance that resampling has inevitably introduced, further studies should be focused on how to circumvent resampling while maintaining an acceptable ESS; On the other hand, novel resampling schemes should be developed to address the trade-off between particle diversity and variance reduction.

We used a stepwise multiple regression analysis to investigate whether a combination of frequency measures explained extra variance in the RT data.

Contrary to the GMH, however, the survivor group also exhibited significantly slower growth over the first 6 d post-settlement than the intermediates or 6 7 d old recruits, once the extra variance due to differing water temperatures was controlled for (Table 4), reflecting consistently higher fitness at low juvenile growth (Fig. 4b).

In English and French, it has also been found that word frequencies based on written texts explain a few percentages of extra variance in visual lexical decision data to those based on film subtitles, even though the written frequencies themselves are inferior to the subtitle frequencies.

If there are biological replicates, the count data may have larger variances than expected from the Poisson distribution as biological replicates bring extra variances.

The variance is: Variance includes extra variation due to equating a mixture by a linear expectation.

Nevertheless, determining in what manner cluster effect might be influenced by either outlier hospitals or the extra-variance attributable to the mix of hospitals within the sample is also needed.

A way to mitigate this limitation is to reduce the extra-variance due to differences in case-mix that the model is unable to capture, by modelling the largest hospitals.

The variance may be higher and the standard approaches may not account for the extra variation, underestimating variability [ 7, 10, 35].