On Tuesday 01 July 2003 05:16, M. Edward Borasky wrote: > Unfortunately, the data are *non-negative*, not strictly positive. Zero is > a valid and frequent inter-arrival time. It is, IIRC, the most likely value > of a (negative) exponential distribution.
Not really. Zero+ is the value with highest density in a (negative) exponential distribution, which implies that you should have *no* observed zero's from that distribution. If you have a non-negligible fraction of 0 values, then your data are reasonably described as having a mixed distribution: (1) a discrete component at 0, and (2) a continuous positive component. Kernel (or similar) density estimation is appropriate for the continuous component only. Notice that the same remark applies to any procedure (parametric or non-parametric, using mixtures, etc.) which is based on continuous components only. It *looks* that a wise procedure is to separate out the discrete and the continuos component of your data, and handle them separately. At the end you can "merge" the two parts into Y = p * 0 + (1-p) * X where p is the proportion of 0's, and X represents the continuous component of the random variable. best wishes, Adelchi Azzalini -- Adelchi Azzalini <[EMAIL PROTECTED]> Dipart.Scienze Statistiche, Università di Padova, Italia http://azzalini.stat.unipd.it/ ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help