normalp {MCMC4Extremes} | R Documentation |
Posterior Distribution with Normal Density
Description
MCMC runs of posterior distribution of data with Normal(mu,1/tau)
density, where tau
is the inverse
of variance.
Usage
normalp(data, int=1000)
Arguments
data |
data vector |
int |
number of iteractions selected in MCMC. The program selects 1 in each 10
iteraction, then |
Value
An object of class gumbelp
that gives a list containing the points of posterior distributions of mu
and tau
of the normal distribution, the data, mean posterior, median posterior and the credibility interval of the parameters.
Note
The non-informative prior distribution of these parameters are Normal(0,10000000)
for the parameter mu and Gamma(0.001,0.001)
for the parameter tau
. During the MCMC runs,
screen shows the proportion of iteractions made.
See Also
Examples
# Obtaining posterior distribution of a vector of simulated points
x=rnorm(300,2,sqrt(10))
# Obtaning 1000 points of posterior distribution
ajuste=normalp(x, 200)
# Posterior distribution of river Nile dataset
## Not run: data(Nile)
## Not run: postnile=normalp(Nile,1000)