Sentence examples for summed distances from inspiring English sources

Thus, the shortest summed distances between all the combinations of time series data (in this study, 100 time series data from 100 tube well samples) were calculated and the distance matrix (100 × 100) was created.

Of the distance methods, the neighbor-joining (NJ) method is most theoretically similar to PA in that it seeks to capture the phylogenetic signal by finding the cladogram with the shortest summed distances over all the branches (Saitou and Nei 1987).

Landmark configurations are translated, scaled and rotated so as to minimize the squared, summed distances between the corresponding landmarks of each individual and the mean [ 26].

To test whether the observed clustering is statistically significant, we calculate a p-value by comparing the observed summed distances along the tree against a null distribution produced by randomly permuting TG information of each protein (1000 permutations).

These summed distances provided a metric of the parameter diversity captured in a choice of five parameter sets; we examined one thousand randomly drawn sets of five and chose the set with the highest summed distance.

We adjusted for the effect of allometry (Drake and Klingenberg, 2008) by computing a multivariate regression of shape on centroid size, measured as the square root of the summed distances between each landmark coordinate and the centroid of the landmark configuration (Dryden and Mardia, 1998).

The summed distance for the medoid is, on average, 1.19 times the summed distance for the central spike train.

The function average is even more central, its summed distance is on average 0.87 times the summed distance for the central spike train.

As a measure of how central the central spike train is, the summed distance between it and the other spike trains for the song is compared to the summed distance between the medoid and the spike trains.

Another measure of centrality is the summed distance between a spike train and the spike trains in the collection { u 1, u 2, …, u n }.

Therefore, if the two time series have totally different patterns from each other, then the summed distance can be large, that is their dissimilarity is large.