Sentence examples for captures variables that from inspiring English sources

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As to the actual 30-year climate normal period used, the WMO recommendation (WMO (2010) and Arguez and Vose (2011)) is 1971 2000 which has the advantage of a good data coverage for many areas and, due to its higher actuality, better captures variables that have a trend over time.

Similar(59)

This suggests that survey more effectively captured variables that can explain utilitarian walking than variables that can explain hedonic walking.

Self-identification corresponds to the respondents reported sexual identity, which may also indirectly capture variables that are unmeasured by this study, including disclosure, internalized stigma, or experiences of social stigma.

Adaptation interventions require capturing dynamic variables that change over time and place, and understanding the decision-making processes at the household level leading to action and sustainable change.

As noted above, the difference-in-difference estimator provides a valid estimate of program impact if selection into the program is on the basis of stable characteristics affecting prior and subsequent earnings and employment that are not captured by variables that have been controlled10.

Boosted regression tree modelling combines both regression trees, which build a set of decision rules on the predictor variables by portioning the data into successively smaller groups with binary splits (De'ath, 2007; Elith et al., 2008), and boosting, which selects the tree that minimises the loss of function, to best capture the variables that define the distribution of the input data.

The only remaining explanation is that study region captures differences in variables that have not been specifically recorded, for example the oocyte retrieval procedure.

The proposed rating attempts to capture the main variables that define the behaviour of a buckling column.

15 Due to the nature of its items, the CSHA-CFS may capture some unmeasured variables that may have impacted on function and falls.

PCA summarizes high-dimensionality data by capturing the latent variables that best describe a data set, allowing simple visualization of allele frequency differences among populations.

Thus, while in PCA the first component, i.e. the DI, is composed of those variables that capture greater variability it leaves some variables out of the index.

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