Sentence examples for its variance from from inspiring English sources

Local AAMs (LAAMs) are trained to model a specific facial area and decompose its variance from the rest of the facial variance.

This shows how the complexity of the algorithm can be reduced by an order of magnitude by adopting an extra implicit assumption regarding the wide-sense stationarity of the noise and hence the constancy of its variance from one iteration to the next.

The most accurate method was to retrieve the HR estimate and its variance from the reported results, or to calculate them directly using parameters given by the authors for the univariate analysis: the O− E statistic (difference between numbers of observed and expected events), the confidence interval for the HR, the log-rank statistic or its P-value.

Among the three remaining trials for which data were obtained from the investigators or published reports, we estimated the hazard ratios and variances with a Cox model for one trial 14 and calculated the relative risks and its variances from first principles using tabular data for two trials.

(2) Estimating waiting time and its variance suffers from thrashing.

We estimated the optimal solution by taking the ensemble average of the sampled points at τ 1, and its variance (sigma^{2}) from the squared residuals of (log left( {rA_{text{max} } } right)) at τ 1.

The authors go on to discuss several indirect methods for estimating the log hazard ratio and its variance either from summary trial results or the published survival curves.

According to Sutton et al and Ades at el [ 24, 25], the pooled OR and its sampling variance from the observational studies could be used as the prior in the analysis of RCTs.

The population total and its variance is estimated from any mean by Y ^ = N y ¯ v( Y ^ ) = N 2 v ( y ¯ ).

Domain terms have normal prior distribution centred at 0 (its variance is estimated from the data and has an inverse-gamma prior distribution).

This hypothesis has been tested using bootstraping [ 29, 30], which is a resampling procedure that estimates the properties of an estimator (such as its variance) by sampling from an approximating empirical distribution.