Create a parametric univariate Normal CGF

Builds a CGF for \(Y \sim N(\mu(\theta), \sigma(\theta))\), where mu and sigma are functions (or adaptors) of theta.

Both mu(theta) and sigma(theta) may return a scalar or a vector. If they return vectors, they must have the same length L and are interpreted in the same vectorised way as other univariate model CGFs in this package.

Usage

NormalModelCGF(mu, sigma, iidReps = "any", ...)

GaussianModelCGF(mu, sigma, iidReps = "any", ...)

Arguments

mu

Function/adaptor mapping theta -> mean(s).

sigma

Function/adaptor mapping theta -> sd(s).

iidReps

Either "any" or a positive integer (replication semantics).

...

Passed through to CGF creation.