Description Usage Arguments Details Value Author(s) References See Also Examples
The function provides information on the estimated effective dimension reduction (EDR) space.
1 2 |
object |
Object of class |
m |
Dimension of the effective dimension reduction (EDR) space. |
R |
If code |
... |
Additional parameters will be ignored |
Provides information on the estimated effective dimension reduction (EDR) space.
The first m
basis vectors and the cummulative sum of normalized eigenvalues of matrix
object$bhat
are given. If R
is specified the distance
||R (I- \hat{P}_m)||/||R|| \mbox{with} \hat{P}_m = U_m^T U_m , \hat{R}_m=U_m Λ V^T
and the distance specified by Li (1992) are computed.
Returns a list with components
Rhat |
(First) m eigenvectors of the estimated EDR space. |
cumlam |
Cummulative sum of first m eigenvalues of |
loss1 |
If |
loss2 |
The distance specified by Li (1992). |
Joerg Polzehl, polzehl@wias-berlin.de
M. Hristache, A. Juditsky, J. Polzehl and V. Spokoiny (2001). Structure adaptive approach for dimension reduction, The Annals of Statistics. Vol.29, pp. 1537-1566. \ J. Polzehl, S. Sperlich (2009). A note on structural adaptive dimension reduction, J. Stat. Comput. Simul.. Vol. 79 (6), pp. 805–818. \ K.-C. Li (1992). On principal Hessian directions for data visualization and dimension reduction: another application of Stein's lemma, JASA, Vol. 87, pp. 1025-1039.
edr
, edr.R
, print.edr
, plot.edr
1 2 3 | require(EDR)
## Not run: demo(edr_ex1)
## Not run: demo(edr_ex2)
|
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