Description Usage Arguments Details Value Author(s) References See Also Examples
The bandwidth of the kernel is choose for normal model and normal kernel in such a way a contaminated point costant
times away from the mean of the distribution in scale units and mass level
has a weight no bigger than weight
.
1 2 3 | wle.smooth(weight=0.31,costant=3,level=0.2,
dimension=1,raf="HD",interval=c(0.00001,0.5),
tol=10^-6,max.iter=1000)
|
weight |
weights associated to an observation that is |
costant |
times the contaminated point mass is away from the mean of the distribution in scale units. |
level |
mass of the contaminated point. |
dimension |
dimension of the normal distribution. |
raf |
type of Residual adjustment function to be use:
|
interval |
interval from which to search the root. |
tol |
the absolute accuracy to be used to achieve convergence of the algorithm. |
max.iter |
maximum number of iterations. |
The wle.smooth
use uniroot
function to solve the non linear equation. No handling error is provided yet. For the Symmetric Chi-Squared Disparity RAF you should use weight=0.2
and interavl=c(0.1,1)
to have a solution.
wle.smooth
returns an object of class
"wle.smooth"
.
Only print method is implemented for this class.
The object returned by wle.smooth
is a list with four components: root and f.root give the location of the root and the value of the function evaluated at that
point. iter and estim.prec give the number of iterations used and an approximate estimated precision for root.
root
is the value of the bandwidth.
Claudio Agostinelli
Agostinelli, C., (1998) Inferenza statistica robusta basata sulla funzione di verosimiglianza pesata: alcuni sviluppi, Ph.D. thesis, Department of Statistics, University of Padova.
Markatou, M., Basu, A. and Lindsay, B.G. (1998) Weighted likelihood estimating equations with a bootstrap root search. Journal of the American Statistical Association, 93, 740-750.
Agostinelli, C., and Markatou, M., (2001) Test of hypotheses based on the Weighted Likelihood Methodology, Statistica Sinica, vol. 11, n. 2, 499-514.
uniroot, uniroot
: one dimensional root finding.
1 2 3 | library(wle)
wle.smooth()
|
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