Weighted Median. The directional weighted median filter DWMF proposed in calculates the sum of absolute differences between the gray scale values of the pixels along four directions north-south northeast-southwest northwest-southeast and east-west in the selected window. Then the weighted median is the interpolated amt.
For instance let us assume equity consists of 80 of a portfolio and debt balance 20. Where the weight is the number of times that a given data appears. It factors in the number of times the two values in the middle subset of a table with an even number of rows appear.
That corresponds to a weight factor of 50.
Where the weight is the number of times that a given data appears. The formula for finding the weighted average is the sum of all the variables multiplied by their weight then divided by the sum of the weights. As for weighted mean based on lagged market capitalization I use egen wmEarnings. Feb 04 2020 WeightedStats includes four functions mean weighted_mean median weighted_median which accept lists as arguments and two functions numpy_weighted_mean numpy weighted_median which accept either lists or numpy arrays.
