dax42 <Dax42 <at> web.de> writes: : : Dear list, : : I have got an array with observational values t and I would like to fit : a geometric distribution to it. : As I understand the geometric distribution, there is only one : parameter, the probability p. I estimated it by 1/mean(t).
p=1/EX if the geometric distribution starts at 1 but in R the geometric distribution starts at 0. That is, in R the geometric distribution is the number of failures before a success, not the number of trials including the success. If X is a geometric random variable then EX = 0p + (EX+1)(1-p) and solving for EX gives 1/p-1. : : Now I plotted the estimated density function by : plot(ecdf(t),do.points=FALSE,col.h="blue"); : : and I would like to add the geometric distribution. This should be : possibly with the function pgeom(). : : Unfortunately I do not understand what is meant by the argument q, : "vector of quantiles representing the number of failures in a sequence : of Bernoulli trials before success occurs" according to R help. : : I am familiar with quantiles, but why do I need them here? : Does anybody know what this means? What am I supposed to do? The quantiles are just the values of the geometric random variable. That is if you have a data vector x in which the ith element of x is the ith observation (where each observation is the number of failures before a success, viz. a non-negative integer) then dgeom(x, .2) would give a vector of density values assuming the probability of a success is .2 . ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
