scrBesag: Simultaneous credible band computation
In hypergsplines: Bayesian model selection with penalised splines and hyper-g prior

Calculates a series of simultaneous credible bounds for one parameter type.

1	scrBesag(samples, level = 0.95)

`samples`	m by n matrix where m is the number of parameters, n is the number of samples and hence each (multivariate) sample is a column in the matrix `samples`
`level`	the credible level (default: 0.95)

matrix with ‘lower’ and ‘upper’ columns

Thomas Kneib

J. Besag, P. Green, D. Higdon, K. Mengersen (1995): Bayesian Methods for Nonlinear Classification and Regression, Statistical Science 10/1, 3–66, http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.27.8854

hypergsplines documentation built on May 2, 2019, 6:14 p.m.