normalp {MCMC4Extremes} | R Documentation |
MCMC runs of posterior distribution of data with Normal(mu,1/tau)
density, where tau
is the inverse
of variance.
normalp(data, int=1000)
data |
data vector |
int |
number of iteractions selected in MCMC. The program selects 1 in each 10
iteraction, then |
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.
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.
# 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)