Sentence examples for most commonly applied methods from inspiring English sources

Plate load test (PLT) is one of the most commonly applied methods to determine this parameter.

The Markov switching model due to Hamilton (1989) is one of the most commonly applied methods for identifying business cycles in economic data.

Still, among the supervised learning algorithms, HMMs and Bayes networks are thus far the most commonly applied methods in the area of context recognition.

Based on frequency use, the most commonly applied methods are still principal component analysis (PCA) [2], and [34], partial least squares (PLS) [4, 5] and [45], linear discriminant analysis (LDA) [8], and sliced inverse regression (SIR) [3].

Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation.

Because t-statistics based statistical tests take technical variations into consideration when determining true biological differences, they have become one of the most commonly applied methods to determine differentially expressed genes from microarray results.

The most commonly applied method for aggregated data to test for spatial autocorrelation (n = 13 studies) was Moran's I (Moran 1950) for which a value >1 indicates presence of spatial autocorrelation.

As for many other complexes, including a majority of complexes with amino acids and peptides, the irreversible part of the reaction is quite rapid (e.g. t1/2 <5 min for glygly), which excludes the use of the most commonly applied method based only on potentiometric titration [39 41].

We used Landsat imagery as a reference; since it is, by and large, the most commonly applied method to support multi-temporal delineation between forest and non-forest cover types by both manual (e.g. Townshend et al. 1995) and unsupervised automated or semi-automated (e.g. Achard et al. 2002) classification procedures and their combinations (e.g. McRoberts et al. 2014; Sannier et al. 2014).

The most commonly applied method has been to rank all transcripts according to their Pearson correlation with different metabolites (Urbanczyk-Wochniak et al., 2003).

This approach is the most commonly applied method for valuing preferences for non-market goods with thousands of applications conducted to date [ 10].