3 citations · 5 across the 5 of their papers we have counts for
7 papers
Introducing Inner Nested Sampling
H. R. N. van Erp, R. O. Linger, P. H. A. J. M. van Gelder
In this paper we will give a Monte Carlo algorithm by which the moments of a functions of Dirichlet probability distributions can be estimated. This algorithm is called Inner Neste…
An Outline of the Bayesian Decision Theory
H. R. N. van Erp, R. O. Linger, P. H. A. J. M. van Gelder
In this paper we give an outline on the Bayesian Decision Theory.
Exploring Beta-Like Distributions
H. R. N. van Erp, R. O. Linger, P. H. A. J. M. van Gelder
The most well known probability distribution of probabilities is the Beta distribution. If we have observed `successes', each having a probability , and `failures', ea…
Constructing cartesian splines
H. R. N. van Erp, R. O. Linger, P. H. A. J. M. van Gelder
We introduce here Cartesian splines or, for short, C-splines. C- splines are piecewise polynomials which are defined on adjacent Cartesian coordinate systems and are Cr continuous…
Constructing Explicit B-Spline
R. O. Linger, H. R. N. van Erp, P. H. A. J. M. van Gelder
We introduce here a direct method to construct multivariate explicit B-spline bases. B-splines are piecewise polynomials, which are defined on adjacent tetrahedra and which are $C^…
Fact Sheet Research on Bayesian Decision Theory
H. R. N. van Erp, R. O. Linger, P. H. A. J. M. van Gelder
In this fact sheet we give some preliminary research results on the Bayesian Decision Theory. This theory has been under construction for the past two years. But what started as an…
Deriving Proper Uniform Priors for Regression Coefficients, Part II
H. R. N. van Erp, R. O. Linger, P. H. A. J. M. van Gelder
It is a relatively well-known fact that in problems of Bayesian model selection improper priors should, in general, be avoided. In this paper we derive a proper and parsimonious un…