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  2. Weighted median - Wikipedia

    en.wikipedia.org/wiki/Weighted_median

    The weighted median is shown in red and is different than the ordinary median. In statistics, a weighted median of a sample is the 50% weighted percentile. [1] [2] [3] It was first proposed by F. Y. Edgeworth in 1888. [4] [5] Like the median, it is useful as an estimator of central tendency, robust against outliers. It allows for non-uniform ...

  3. Hodges–Lehmann estimator - Wikipedia

    en.wikipedia.org/wiki/Hodges–Lehmann_estimator

    In statistics, the Hodges–Lehmann estimator is a robust and nonparametric estimator of a population's location parameter.For populations that are symmetric about one median, such as the Gaussian or normal distribution or the Student t-distribution, the Hodges–Lehmann estimator is a consistent and median-unbiased estimate of the population median.

  4. Inverse-variance weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse-variance_weighting

    For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().

  5. Three-point estimation - Wikipedia

    en.wikipedia.org/wiki/Three-point_estimation

    These values are used to calculate an E value for the estimate and a standard deviation (SD) as L-estimators, where: E = (a + 4m + b) / 6 SD = (b − a) / 6. E is a weighted average which takes into account both the most optimistic and most pessimistic estimates provided. SD measures the variability or uncertainty in the estimate.

  6. Inverse probability weighting - Wikipedia

    en.wikipedia.org/wiki/Inverse_probability_weighting

    An alternative estimator is the augmented inverse probability weighted estimator (AIPWE) combines both the properties of the regression based estimator and the inverse probability weighted estimator. It is therefore a 'doubly robust' method in that it only requires either the propensity or outcome model to be correctly specified but not both.

  7. Male humpback whale makes record-breaking migration - AOL

    www.aol.com/news/humpback-whale-makes-record...

    For example, one of the humpback populations in the North Pacific migrates to feed in waters around Alaska during the summer and spends the winter in waters around the Hawaiian Islands to breed, ...

  8. Dow Jones-UBS Commodity Index Fact Sheet

    images.huffingtonpost.com/2011-05-02-Dow...

    — The index represents 19 commodities, which are weighted to account for economic significance and market liquidity. — Weighting restrictions on individual commodities and commodity groups promote diversification. Performance Total Return (%) Annualized Total Return (%) Index Name 1-Month 3-Month YTD 2010 1-Year 3-Year 5-Year 10-Year Since ...

  9. Winsorized mean - Wikipedia

    en.wikipedia.org/wiki/Winsorized_mean

    A winsorized mean is a winsorized statistical measure of central tendency, much like the mean and median, and even more similar to the truncated mean.It involves the calculation of the mean after winsorizing — replacing given parts of a probability distribution or sample at the high and low end with the most extreme remaining values, [1] typically doing so for an equal amount of both ...