poisdp {Bolstad} | R Documentation |
Poisson sampling with a discrete prior
Description
Evaluates and plots the posterior density for mu, the mean rate
of occurance in a Poisson process and a discrete prior on mu
Usage
poisdp(y.obs, mu, mu.prior, ret = FALSE)
Arguments
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. |
ret |
if true then the likelihood and posterior are returned as a list. |
Value
If ret is true, then 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 |
See Also
poisgamp
poisgcp
Examples
## 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, ret=TRUE)
## 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)
[Package
Bolstad version 0.2-14
Index]