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The lower weighted median is 2 with partition sums of 0.49 and 0.5, and the upper weighted median is 3 with partition sums of 0.5 and 0.25. In the case of working with integers or non-interval measures, the lower weighted median would be accepted since it is the lower weight of the pair and therefore keeps the partitions most equal. However, it ...
A weight function is a mathematical device used when performing a sum, integral, or average to give some elements more "weight" or influence on the result than other elements in the same set. The result of this application of a weight function is a weighted sum or weighted average.
A kernel smoother is a statistical technique to estimate a real valued function: as the weighted average of neighboring observed data. The weight is defined by the kernel, such that closer points are given higher weights. The estimated function is smooth, and the level of smoothness is set by a single parameter.
The median of three vertices in a tree, showing the subtree formed by the union of shortest paths between the vertices. Every tree is a median graph. To see this, observe that in a tree, the union of the three shortest paths between pairs of the three vertices a, b, and c is either itself a path, or a subtree formed by three paths meeting at a single central node with degree three.
A weighting curve is a graph of a set of factors, that are used to 'weight' measured values of a variable according to their importance in relation to some outcome. An important example is frequency weighting in sound level measurement where a specific set of weighting curves known as A-, B-, C-, and D-weighting as defined in IEC 61672 [1] are used.
The time-weighted rate of return measures how your investments have performed in a vacuum. Basically, for the assets that you purchased, it determines how much have they gained or lost value.
At the time, WW had also launched the WeightWatchers Clinic, an online program that connects you with clinicians and care coordinators to help tailor your weight loss plan and prescribe weight ...
G is a graph, w is a weights array of all edges in the graph G. [6] function MBST(graph G, weights w) E ← the set of edges of G if | E | = 1 then return E else A ← half edges in E whose weights are no less than the median weight B ← E - A F ← forest of G B if F is a spanning tree then return MBST(G B,w) else return MBST((G A) η, w) F