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  2. Weighted median - Wikipedia

    en.wikipedia.org/wiki/Weighted_median

    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 ...

  3. N50, L50, and related statistics - Wikipedia

    en.wikipedia.org/wiki/N50,_L50,_and_related...

    For example: If L = (2, 2, 2, 3, 3, 4, 8, 8), then L' consists of six 2's, six 3's, four 4's, and sixteen 8's. That is, L' has twice as many 2s as L; it has three times as many 3s as L; it has four times as many 4s; etc. The median of the 32-element set L' is the average of the 16th smallest element, 4, and 17th smallest element, 8, so the N50 is

  4. Weight function - Wikipedia

    en.wikipedia.org/wiki/Weight_function

    The result of this application of a weight function is a weighted sum or weighted average. Weight functions occur frequently in statistics and analysis, and are closely related to the concept of a measure. Weight functions can be employed in both discrete and continuous settings.

  5. Weighted arithmetic mean - Wikipedia

    en.wikipedia.org/wiki/Weighted_arithmetic_mean

    When a weighted mean is used, the variance of the weighted sample is different from the variance of the unweighted sample. The biased weighted sample variance σ ^ w 2 {\displaystyle {\hat {\sigma }}_{\mathrm {w} }^{2}} is defined similarly to the normal biased sample variance σ ^ 2 {\displaystyle {\hat {\sigma }}^{2}} :

  6. Kernel smoother - Wikipedia

    en.wikipedia.org/wiki/Kernel_smoother

    Kernel average smoother example. The idea of the kernel average smoother is the following. For each data point X 0, choose a constant distance size λ (kernel radius, or window width for p = 1 dimension), and compute a weighted average for all data points that are closer than to X 0 (the closer to X 0 points get higher weights).

  7. Kernel (statistics) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(statistics)

    In statistics, especially in Bayesian statistics, the kernel of a probability density function (pdf) or probability mass function (pmf) is the form of the pdf or pmf in which any factors that are not functions of any of the variables in the domain are omitted. [1] Note that such factors may well be functions of the parameters of the

  8. Weighting curve - Wikipedia

    en.wikipedia.org/wiki/Weighting_curve

    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.

  9. Theil–Sen estimator - Wikipedia

    en.wikipedia.org/wiki/Theil–Sen_estimator

    A variation of the Theil–Sen estimator, the repeated median regression of Siegel (1982), determines for each sample point (x i, y i), the median m i of the slopes (y j − y i)/(x j − x i) of lines through that point, and then determines the overall estimator as the median of these medians. It can tolerate a greater number of outliers than ...