Apologies for the bombardment. The following has substance for discrete random variables and samples with many ties. The Gretl function "ranking" does the following: << ranking Output:     same type as input Argument:     y  (series or vector) Returns a series or vector with the ranks of y. The rank for observation i is the number of elements that are less than y_i plus one half the number of elements that are equal to yi. The function performs as stated in Help. To my understanding the above is consistent with the concept of the "mid-Distribution Function" introduced I think by Em. Parzen and associates. If we take the resulting series and divide by sample size, we get a series where we assign an empirical probability to each observation i. But these are probabilities consistent with the empirical mid-distribution function. But, there is not a Gretl function like, say, << rankingalt Output:     same type as input Argument:     y  (series or vector) Returns a series or vector with the ranks of y. The rank for observation i here is the number of elements that are less or equal than y_i. See also ranking. So while using the "ecdf" Gretl function we get the unique values of the empirical distribution function (as if it internally uses the non-existent function "rankingalt"), if one wants to obtain a series having the length of the sample, where at each observation i a probability is assigned that is consistent with the empirical distribution function (and not the empirical mid-distribution function), one cannot achieve that, at least not in one obvious stroke. It is not clear whether the empirical mid-distribution function is the suitable tool to be used in all cases (my case relates to mixed Copulas), so I was wondering whether Gretl could acquire a function like "rankingalt" above. Thanks. -- Alecos Papadopoulos PhD Athens University of Economics and Business web: alecospapadopoulos.wordpress.com/