Gaussian errors

loglik = new(loglik_std, om, terms, y, x)

This is a standard model which has the form $$y = \langle \phi(x), \theta \rangle + \varepsilon, \varepsilon \sim N(0,\sigma^2)$$ where \(\phi(x)\) is the basis, \(\theta\) is the coefficient vector, \(\varepsilon\) is an unseen noise vector. The parameter vector is of length 1 where para \(= \log(\sigma)\). It is a slower (sometimes) version of loglik_gauss but allows for complete marginal inference.

Arguments

om

an outermod instance to be referred to

terms

a matrix of terms, must have as many columns as dims in om

y

a vector of observations

x

a matrix of predictors, must have as many columns as dims in om and the same number of rows as y

Value

no returns, this is a class which contains methods

See also

base class: lpdf