alpha*N(0,sigma^2) + (1-alpha)*N(0,k^2*sigma^2)
accalc(alpha, k, effects)
alpha
,
k
, the effects
and the posterior probabilities.
The function
accalc
calls a C function which was adapted from
Stephenson et al. (1989). The posterior probabilities are calculated
by an analytical method if there are 16 effects or less, and numerical
integration for more than 16 effects. The function
accalc
is called
by the function
acplot
which generates active contrast plots.
Box and Meyer (1986), An analysis for unreplicated fractional
factorials, Technometrics, 28, 11-18.
Haaland, P. D. (1989),
Experimental Design in Biotechnology,
New York: Marcel Dekker.
Stephenson, W. R., F. L. Hulting, and K. Moore (1989), Posterior
probabilities for identifying active effects in unreplicated
experiments,
Journal of Quality Technology
21, 202-212.
buffer.fac <- fac.aov(buffer.df) accalc(.2,10,buffer.fac$feffects)