Sentence examples for most statistical approaches from inspiring English sources

To date, most statistical approaches have estimated spatial or temporal trends using stationary probability density functions [6] [9] and spatial models [10], which provide insights into the cause-effect relationships favouring disease transmission.

Most statistical approaches use separate pair-wise comparisons of methods in these situations [ 6].

This makes it different from most statistical analytic approaches, but there are some useful comparisons to be made with other methods.

The local binary pattern (LBP) is one of the most successful statistical approaches for texture classification due to its gray-scale and rotation invariance, this feature reflects the local texture of the image.

For each, the most popular statistical approaches are reviewed.

Most frequently, statistical approaches are used to develop these classifiers.

Outcome measures are summarized in Table 3. Below, we describe the most probable statistical approaches in the evaluation of associations between self-reported sleep disturbances and exposures.

We hope this step-by-step guide and the attached flowchart will assist readers in carrying out the most appropriate statistical approaches for these issues, and thereby avoid the common pitfalls of such analysis.

The most common statistical approach was the two-staged hypothesis testing method, with Simon's methods (optimal and minimax) being the preferred methods.

Weighted meta-analyses are widely regarded as the most appropriate statistical approach for comparing data sets from studies with variable experimental designs.

An additional and fundamental question that remains to be determined before any analysis concerns the choice of the most convenient statistical approach that should be used to identify the best HKG or set of HKG.