asymmetricIntervals: Compute Asymmetric Intervals
In popKorn: For interval estimation of mean of selected populations

Description Usage Arguments Details Value References See Also Examples

This function will compute asymmetric intervals for the mean of the selected populations.

1	asymmetricIntervals(X, alpha = 0.05, k = 2, var = NULL, eps = 0.1)

`X`	is a matrix or data frame that contains the responses. Each column represents a different population.
`alpha`	denotes the significance level of the intervals to be formed.
`k`	corresponds to the number of populations to be selected.
`var`	denotes the common variance of the populations from which the data is drawn. If this is NULL (the default), then the variance will be estimated from the data. If it is known, then it should be provided as a scalar.
`eps`	The grid size that is to be set up.

This function will compute the optimal lambda and c to be used to shrink the interval for the selected populations.

This function returns a matrix with k rows and 3 columns. This is similar to the output of the predict.lm function of R.

Claudio Fuentes, George Casella and Martin Wells (2013). Interval estimation for the mean of the selected populations (Submitted).

Vik Gopal and Claudio Fuentes (2013). kPop: An R package for interval estimation of selected populations. useR! 2013.

bonferroniIntervals, bootstrapIntervals

set.seed(18)
p <- 10; n <- 10
Xmat <- matrix(rnorm(p*n), nrow=n, ncol=p)
colnames(Xmat) <- paste("p.", 1:p, sep="")
asymmetricIntervals(Xmat, alpha=0.1, k=4)