We applied the central limit theorem and interval estimation theories to approximate the original dataset distribution with a sample set [13].
Sample text:```The above estimator generalizes the estimator in Sriperumbudur et al., 2017 to conditional densities.```
Sample intent: method
Sample text:```Our results are in agreement with other studies which reported the presence of plasticizer residues in water stored in bottles [10,12].```
Sample intent: result



Sample text:```The items are internally consistent and reproducible and the questionnaire may therefore be considered to have at least as favourable levels of reliability as clinical scores used to assess outcomes (Koran 1975).```
Sample intent: result



Sample text:```This section contains a generalisation of the basic results on multifractal products of stochastic processes developed in Kahane (1985), Kahane (1987) and Mannersalo et al (2002).```
Sample intent: method



Sample text:```Our results confi rm previous studies that reached the same conclusion (Boushey et al 1994; Vermeulen et al 2000; Till et al 2005; Marcucci et al 2005).```
Sample intent: result



Sample text:```The above estimator generalizes the estimator in Sriperumbudur et al., 2017 to conditional densities.```
Sample intent: method
Sample text:```In this study, we generalized previous results regarding the quasi-Gaussian shape and the scalar property using the SBF model [13,21,52].```
Sample intent: result



Sample text:```We used longitudinal sequence samples for 15 patients from two independent studies [13,22].```
Sample intent: background



Sample text:```Estimation of overall mortality ratio (relative risk) was carried out using the random e ects model according to DerSimonian and Laird [9].```
Sample intent: background



Sample text:```5 concentrations were computed for each participant using a hierarchical spatiotemporal model fit with a pragmatic estimation procedure described elsewhere [30,31].```
Sample intent: background



Sample text:```The above estimator generalizes the estimator in Sriperumbudur et al., 2017 to conditional densities.```
Sample intent: method



Sample text:```Discrepancies analogous to those between our results and those of simulations have, indeed, recently been observed in the case of the binary perceptron [18], the pspin interaction spin glass [19], and in the case of fluctuating manifolds in random media [20], where dynamically frozen phases were observed in regions of parameter space in which static approaches yielded ergodic phases.```
Sample intent: result



Sample text:```The merging is based on the increase in the weighted-bycounts entropy [1] and is stopped by a threshold indicating the minimum number of training samples required to estimate a weight distribution.```
Sample intent: method



Sample text:```While this method is known to be generally reliable, there are some questions about the representativeness of the data used [25].```
Sample intent: background



Sample text:```In-between methods can be subdivided into linear approximations [12,24] and quadratic interpolation methods [22,23,25–27] based on the degree of the polynomial approximation employed.```
Sample intent: method



Sample text:```The items are internally consistent and reproducible and the questionnaire may therefore be considered to have at least as favourable levels of reliability as clinical scores used to assess outcomes (Koran 1975).```
Sample intent: result