# PofCSLt.bootstrap5: Parametric Bootstrap for Computing L-best PCS In PCS: Calculate the Probability of Correct Selection (PCS)

 PofCSLt.bootstrap5 R Documentation

## Parametric Bootstrap for Computing L-best PCS

### Description

Parametric bootstrap for computing L-best PCS. This function is called by the wrapper PCS.boot.np.

### Usage

```PofCSLt.bootstrap5(theta, T, L, B, SDE, dist = c("normal", "t"),
df = 14, trunc = 6, est.names = c("O"))
```

### Arguments

 `theta` Vector of statistics (or parameters) from which it is desired to select the top t of them `T` Vector of the number of statistics (or parameters) desired to be selected `L` Vector of L-best selection parameters `B` Bootstrap sample size `SDE` Standard error of the statistics theta (row-wise) `dist` Distributional assumption used for estimating PCS `df` Common degrees of freedom for one of the t-statistics in theta; the parameter is only used if dist="t" `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 `est.names` Kind of shrinkage estimator employed. Default estimator is "O" for the Olkin estimator. Other estimators will be considered for future releases.

### Value

An array, the non-empty part of which is a matrix whose rows are the entries of L and whose columns are the entries of T.

### Author(s)

Jason Wilson <jason.wilson@biola.edu>

### References

Cui, X.; Zhao, H. and Wilson, J. 2010. Optimized Ranking and Selection Methods for Feature Selection with Application in Microarray Experiments. Journal of Biopharmaceutical Statistics. Volume 20, No. 2, pp. 223-239. https://docs.google.com/a/biola.edu/viewer?a=v&pid=sites&srcid=YmlvbGEuZWR1fGphc29ud2lsc29ufGd4OjY0ZTJkNDNlMzNiNjE0ZDg

`PCS.boot.par`