Sentence examples for detailed variance from inspiring English sources

The process model has to indicate the system of rules and responsibilities of actors across the organization, facilitate the assessment of resource consumption accurately, facilitate allocation of resources among units by exemplifying a profile capacity usage, and enable the realization of a detailed variance analysis [ 52].

Other possible methodological development lines for further studies include the implementation of risk adjustment and volume association models as one model, relaxation of the Poisson assumption, incorporation of a more detailed variance structure, and models for responses other than binary ones.

To investigate the inter-placental variation of methylation in more detail, variance level of probes for the third trimester was plotted against the first trimester.

Detailed data on variance in population size in the context of biological control are scarce, which limits the power to quantify the intensity of stochastic processes during establishment phase.

The processes, sorption-desorption and microbial decomposition (DOC production and mineralization) are found to contribute most to the variance in DOC export based on a detailed variance-based Sobol sensitivity analysis (SA) at grid cell-level.

Detailed time domain, Allan variance, and probability density function analysis revealed that both ARW and ARRW are of Gaussian type and Coriolis-uncorrelated, showing stable in-operational noise performance of the reported gyroscope.

The protein ratios of time-course groups versus vehicle controls were computed by aggregating the AUC data on peptide levels to protein levels using a weighting model based on relative variances, as detailed in the Supporting Information.

We separate the third explanation from the first and second by controlling for major occupation group effects from both spouses, i.e., indicators such as 1[husband's occupation is "Construction Trades"], and measures of both spouses' detailed occupations' time series earnings variance, as well as the covariance of earnings for their occupation pair.

In this context, the prediction filters are often optimized by minimizing the detail signal variance through mean square criteria [15, 20].

Thus, unlike previous studies where prediction has been separately optimized by minimizing an ℓ2 criterion (i.e., the detail signal variance), we focus on the minimization of an ℓ1 criterion.

See [ 22- 24] for details on variance pruning.