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, ...)
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. |
... |
additional arguments that are passed to |
Value
A list will be returned with the following components:
likelihood |
the scaled likelihood function for |
posterior |
the posterior probability of
|
mu |
the vector of possible
|
mu.prior |
the associated
probability mass for the values in |
See Also
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)
## 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 0.2-41 Index]