logpr_gauss: Gaussian prior

In outerbase: Outer Product Regression

Gaussian prior

Description

logpr = new(logpr_gauss, om, terms)

This is a standard model of coefficients which has them as drawn independently from

θ_i \sim N(0, ρ c_i)

where c_i is the variance supplied by om for the ith term. The parameter vector is of length 1 where ρ= exp(para[0]).

Arguments

om	an outermod instance to be referred to
terms	a matrix of terms, must have as many columns as dims in om

Value

no returns, this is a class which contains methods

See Also

base class: lpdf

outerbase documentation built on June 9, 2022, 5:08 p.m.