| DesignM {sdPrior} | R Documentation |
Computing Designmatrix for Splines
Description
This function computes the design matrix for Bayesian P-splines as it would be done in BayesX. The implementation currently on works properly for default values (knots=20, degree=3).
Usage
DesignM(x, degree = 3, m = 20, min_x = min(x), max_x = max(x))
Arguments
x |
the covariate vector. |
degree |
of the B-splines, default is 3. |
m |
number of knots, default is 20. |
min_x |
the left interval boundary, default is min(x). |
max_x |
the right interval boundary, defalut is max(x). |
Value
a list with design matrix at distinct covariates, design matrix at all observations, index of sorted observations, the difference matrix, precision matrix and the knots used.
Author(s)
Nadja Klein
References
Stefan Lang and Andy Brezger (2004). Bayesian P-Splines. Journal of Computational and Graphical Statistics, 13, 183–212.
Belitz, C., Brezger, A., Klein, N., Kneib, T., Lang, S., Umlauf, N. (2015): BayesX - Software for Bayesian inference in structured additive regression models. Version 3.0.1. Available from http://www.bayesx.org.