b.CV.MBC {DOvalidation} | R Documentation |
Least Squares Cross-Validation for Multiplicative Bias Corrected Hazard Estimators
Description
Bandwidth selection for multiplicatively bias corrected local linear hazard estimation using least squares cross-validation
Usage
b.CV.MBC(grid.b, nb , K = "sextic", xi, Oi, Ei, wei = "same")
Arguments
grid.b |
Optional. A vector of bandwidths to minimise the cross-validation score. If not specified it will be considered an equally-spaced grid of |
nb |
Optional. The number of bandwidths used to minimise the cross-validation score. If "grid.b" is provided then the argument "nb" will be ignored (if specified). |
K |
Indicates the kernel function to be considered in the local linear hazard estimator. Choose between values "epa" (for the epanechnikov kernel) or "sextic" (see details of |
xi |
Vector of time points where the count data are given. |
Oi |
Vector with the number (counts) of occurrences observed at each time point (xi). |
Ei |
Vector with the observed exposure at each time point (xi). |
wei |
Indicates the weights used in the cross-validation score. Choose between the value "exposure" or "same". See details below. |
Details
It is assumed that the data are given as count data i.e. number of occurrences and exposures.
If the cross-validation score is strictly increasing or decreasing then a warning will be shown together with the cross-validated bandwidth (in this case one of the extremes in "grid.b").
The cross-validation score is defined with two different weighting functions. This is controlled with the parameter wei
. By default wei="exposure"
that means that only areas where the exposure is significant contribute to the criterion. Specify wei="same"
to allow all time points contribute the same to the criterion (see Gamiz et al. 2017).
Value
bcv |
The cross-validated bandwidth. |
ind.cv |
The position of the cross-validated bandwidth into "grid.b". |
cv.values |
The values of the cross-validation score for each bandwidth in "grid.b". |
b.grid |
The grid of bandwidths where the cross-validation score has been evaluated. |
Author(s)
Gamiz, M.L., Martinez-Miranda, M.D. and Nielsen, J.P.
References
Gamiz, M.L., Martinez-Miranda, M.D. and Nielsen, J.P. (2017). Multiplicative local linear hazard estimation and best one-sided cross-validation. Available at http://arxiv.org/abs/1710.05575
Nielsen, J.P. and Tanggaard, C. (2001). Boundary and bias correction in kernel hazard estimation. Scandinavian Journal of Statistics, 28, 675-698.
See Also
Examples
data(Iceland)
Oi<-Iceland$D
Ei<-Iceland$E
ti<-40:110 # time is age and it goes from 40 to 110 years
my.bs<-seq(50,80,length.out=30)
res.cv<-b.CV.MBC(grid.b=my.bs,K="sextic",xi=ti,Oi=Oi,Ei=Ei,wei="same")
bcv<-res.cv$bcv
cv.values<-res.cv$cv.values
plot(my.bs,cv.values,main="Cross-validation score",xlab="Bandwidth")
print(paste("The cross-validated bandwidth is:", bcv,sep=" "))