Zncsspline {dae} | R Documentation |
Calculates the design matrix, Z, of the random effects for a
natural cubic smoothing spline as described by Verbyla et al., (1999).
An initial design matrix,
\bold{\Delta} \bold{\Delta}^{-1} \bold{\Delta}
,
based on the knot points is computed. It can
then be post multiplied by the power of the tri-diagonal matrix
\bold{G}_s
that is proportional to the variance matrix of the
random spline effects. If the power is set to 0.5 then the random
spline effects based on the resulting Z matrix will be independent
with variance \sigma_s^2
.
Zncsspline(knot.points, Gpower = 0, print = FALSE)
knot.points |
A |
Gpower |
A |
print |
A |
A matrix
containing the design matrix.
Chris Brien
Verbyla, A. P., Cullis, B. R., Kenward, M. G., and Welham, S. J. (1999). The analysis of designed experiments and longitudinal data by using smoothing splines (with discussion). Journal of the Royal Statistical Society, Series C (Applied Statistics), 48, 269-311.
Z <- Zncsspline(knot.points = 1:10, Gpower = 0.5)