poisdp {Bolstad} | R Documentation |
Evaluates and plots the posterior density for mu, the mean rate of occurance in a Poisson process and a discrete prior on mu
poisdp(y.obs, mu, mu.prior, ...)
y.obs |
a random sample from a Poisson distribution. |
mu |
a vector of possibilities for the mean rate of occurance of an event over a finite period of space or time. |
mu.prior |
the associated prior probability mass. |
... |
additional arguments that are passed to |
A list will be returned with the following components:
likelihood |
the scaled likelihood function for mu given y.obs |
posterior |
the posterior probability of mu given y.obs |
mu |
the vector of possible mu values used in the prior |
mu.prior |
the associated probability mass for the values in mu |
## simplest call with an observation of 4 and a uniform prior on the ## values mu = 1,2,3 poisdp(4,1:3,c(1,1,1)/3) ## Same as the previous example but a non-uniform discrete prior mu = 1:3 mu.prior = c(0.3,0.4,0.3) poisdp(4,mu=mu,mu.prior=mu.prior) ## Same as the previous example but a non-uniform discrete prior mu = seq(0.5,9.5,by=0.05) mu.prior = runif(length(mu)) mu.prior = sort(mu.prior/sum(mu.prior)) poisdp(4,mu=mu,mu.prior=mu.prior) ## A random sample of 50 observations from a Poisson distribution with ## parameter mu = 3 and non-uniform prior y.obs = rpois(50,3) mu = c(1:5) mu.prior = c(0.1,0.1,0.05,0.25,0.5) results = poisdp(y.obs, mu, mu.prior) ## Same as the previous example but a non-uniform discrete prior mu = seq(0.5,5.5,by=0.05) mu.prior = runif(length(mu)) mu.prior = sort(mu.prior/sum(mu.prior)) y.obs = rpois(50,3) poisdp(y.obs,mu=mu,mu.prior=mu.prior)