Description Usage Arguments Details Value References Examples
View source: R/manifold1Dplus.R
The objective function for the 1D-algorithm.
1 | get1Dobj(w,A,B)
|
w |
A vector of length of |
A |
A √{n} estimate of an estimator's asymptotic covariance matrix. |
B |
A √{n} estimate of the parameter associated with the space we are enveloping. for our purposes this quantity is either the outer product of the MLE of the mean-value submodel parameter vector with itself or the outer product of the MLE of the canonical submodel parameter vector with itself. |
This function evaluates the objective function for the
1D-algorithm at w
, A
, and B
. The maximizer
of this objective function is desired for a problem specific
A
and B
.
Fw |
The value of the objective function for the
1D-algorithm evaluated at |
Cook, R.D. and Zhang, X. (2014). Foundations for Envelope Models and Methods. JASA, In Press.
Cook, R.D. and Zhang, X. (2015). Algorithms for Envelope Estimation. Journal of Computational and Graphical Statistics, Published online. doi: 10.1080/10618600.2015.1029577.
1 2 3 4 5 6 7 8 9 10 11 | ## Not run: library(envlpaster)
data(simdata30nodes)
data <- simdata30nodes.asterdata
nnode <- length(vars)
xnew <- as.matrix(simdata30nodes[,c(1:nnode)])
m1 <- aster(xnew, root, pred, fam, modmat)
avar <- m1$fisher
beta <- m1$coef
U <- beta %o% beta
get1Dobj(w = beta, A = avar, B = U)
## End(Not run)
|
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