prior: Generates 'prior.class' objects.
In mathieucarmassi/CaliCo: Code Calibration in a Bayesian Framework

Description Usage Arguments Details Value Author(s) See Also Examples

prior is a function that generates a prior.class containing information about one or several priors. When several priors are selected, the function prior returns a list of prior.class.

1	prior(type.prior, opt.prior)

`type.prior`	the vector of the prior types selected. For example type.prior=c("gaussian","gamma")
`opt.prior`	list of the hyperparameters relatives to the prior selected. If the first prior selected is Gaussian, the hyperparameters would be the mean and the standard deviation. See Details for further clarifications.

The densities implemented are defined as follow

The Gaussian density:

f(x)=1/(σ*√(2π))exp{-1/2*((x-μ)/σ)^2}

where μ and σ (the mean and the standard deviation) are the two hyperparameters. The vector c(μ,σ^2) is the one looked for in opt.prior.
The Gamma density:

f(x)=1/(k^a*Γ(a))*x^(a-1)*exp(-(x/k))

where a and k (the shape and the scale) are the two hyperparameters. The vector c(a,k) is the one looked for in opt.prior.
The Uniform density:

f(x)=1/(b-a)

where a and b (the upper and the lower bound) are the two hyperparameters. The vector c(a,b) is the one looked for in opt.prior.

prior returns a prior.class object. Two main methods are available:

plot() display the probability density of the prior
print() returns the main information concerning the prior distribution

M. Carmassi

model, calibrate, forecast, sequentialDesign

## Not run: 
#### Only one prior is wanted
## For a Gaussian Prior
gaussian <- prior(type.prior="gaussian",opt.prior=list(c(0.5,0.001)))
plot(gaussian)

#### For several priors
priors <- prior(type.prior=c("gaussian","gamma"),opt.prior=list(c(0.5,0.001),c(5,1)))
plot(priors$Prior1)
plot(priors$Prior2)

## End(Not run)