| PdCSGt.bootstrap.NP2 {PCS} | R Documentation |
Non-Parametric Bootstrap for Computing G-best and d-best PCS
Description
Non-parametric bootstrap for computing G-best and d-best PCS. This function is called by the wrapper PCS.boot.np.
Usage
PdCSGt.bootstrap.NP2(X1, X2, T, D, G, N, trunc = 6)
Arguments
X1 |
k by n1 matrix of data. k is the number of populations and n1 the sample size of the first treatment. |
X2 |
k by n2 matrix of data. k is the number of populations and n2 the sample size of the second treatment. |
T |
Vector of the number of statistics (or parameters) desired to be selected |
D |
Vector of d-best selection parameters |
G |
Vector of G-best selection parameters |
N |
The bootstrap sample size |
trunc |
Number of standard errors below the minimum selected population to disregard in the estimation of PCS; it is a truncation parameter to decrease run time |
Value
A matrix whose rows are the entries of G or D and whose columns are the entries of T. If both G and D are entered, then a list is returned, where the $G element is the G-best matrix, the $d element is the d-best matrix.
Author(s)
Jason Wilson <jason.wilson@biola.edu>
References
Cui, X. and Wilson, J. 2009. A Simulation Study on the Probability of Correct Selection for Large k Populations. Communications in Statistics: Simulation and Computation. 38:6. https://docs.google.com/a/biola.edu/viewer?a=v&pid=sites&srcid=YmlvbGEuZWR1fGphc29ud2lsc29ufGd4OjMxYTdjNjJkNzY3NTU4NzA