On the use of kernel-based nonparametric probability density functions in electrochemical process analysis

Nonparametric statistics deals with random observations whose probability distribution is either not known, or unavailable. This paper illustrates a kernel-based estimation of probability density functions (PDF's) for performance evaluation of electrochemical processes, via three quantitative examples.