Calculates initial optimal bandwidth.

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Description

Calculates initial optimal bandwidth with respect to mean squared error using K-fold cross-validation.

Usage

1
optimize.mse.BW(data, t0,tau,h.grid=seq(.01,2,length=50), folds=3, reps=2)

Arguments

data

n by 5 matrix. A data matrix where the first column is XL = min(TL, C) where TL is the time of the long term event, C is the censoring time, and the second column is DL =1*(TL<C), the third column is XS = min(TS, C) where TS is the time of the short term event, C is the censoring time, the fourth column is DS =1*(TS<C), and the fifth column is the covariate. These are the data used to calculate the estimated probability.

t0

the landmark time.

tau

the residual survival time of interest.

h.grid

The grid of possible bandwidths that the user would like the function to search through. Default is h.grid = seq(.01,2,length=50).

folds

Number of folds wanted for K-fold cross-validation. Default is 3.

reps

Number of repitions wanted of K-fold cross-validation. Default is 2.

Value

h

Selected bandwidth.

Author(s)

Layla Parast

References

Parast, Layla, Su-Chun Cheng, and Tianxi Cai. Incorporating short-term outcome information to predict long-term survival with discrete markers. Biometrical Journal 53.2 (2011): 294-307.