likelihood {bspec} | R Documentation |
Prior, likelihood and posterior
Description
Prior density, likelihood, posterior density, and marginal likelihood
functions for the posterior distributions specified through a
bspec
object.
Usage
dprior(x, ...)
likelihood(x, ...)
marglikelihood(x, ...)
dposterior(x, ...)
## S3 method for class 'bspec'
dprior(x, theta, two.sided=x$two.sided, log=FALSE, ...)
## S3 method for class 'bspec'
likelihood(x, theta, two.sided=x$two.sided, log=FALSE, ...)
## S3 method for class 'bspec'
marglikelihood(x, log=FALSE, ...)
## S3 method for class 'bspec'
dposterior(x, theta, two.sided=x$two.sided, log=FALSE, ...)
Arguments
x |
a |
theta |
a |
two.sided |
a |
log |
a |
... |
currently unused. |
Details
Prior and posterior are both scaled inverse
\chi^2
distributions,
and the likelihood is Normal.
Value
A numeric
function value.
Author(s)
Christian Roever, christian.roever@med.uni-goettingen.de
References
Roever, C., Meyer, R., Christensen, N. Modelling coloured residual noise in gravitational-wave signal processing. Classical and Quantum Gravity, 28(1):015010, 2011. doi: 10.1088/0264-9381/28/1/015010. See also arXiv preprint 0804.3853.
See Also
bspec
,
quantile.bspec
,
expectation
Examples
lhspec <- bspec(lh, priordf=1, priorscale=0.6)
# draw sample from posterior:
posteriorsample <- sample(lhspec)
# plot the sample:
plot(lhspec)
lines(lhspec$freq, posteriorsample, type="b", col="red")
# compute prior, likelihood, posterior:
print(c("prior" = dprior(lhspec, posteriorsample),
"likelihood" = likelihood(lhspec, posteriorsample),
"posterior" = dposterior(lhspec, posteriorsample),
"marginal likelihood"= marglikelihood(lhspec)))