In python, given the distribution (expectedValues), gaussian kernel estimation and p value calculation is provided as follows:
kde = scipy.stats.gaussian_kde(expectedValues)
kdePValue = kde.pdf(observedValue)
My question: Is there a way to calculate poisson kernel density estimation for given distribution (expectedValues) and p value calculation for a given observedValue in python?
Actually I computed the probability as follows: I calculated the mean of expected values and give this mean value to the poisson.pmf by importing scipy.stats
mu = sum(expectedValues)/len(expectedValues)
prob = poisson.pmf(observedValue, mu)