View source: R/computeBoundary.R
computeBoundary | R Documentation |
This function computes the boundary of the decision region in a manner that can be employed in the field, as a table, for example. See section 4.2 of the reference below.
computeBoundary(b1, b0, p, glrTables = NULL, tol=1e-7)
b1 |
The acceptance boundary value (corresponds to the boundary b_1 in the appendix of reference) |
b0 |
The rejection boundary value (corresponds to the boundary b_0 in the appendix of reference) |
p |
The vector of probabilities, (p_0, p_1) with p_0 < p_1. |
glrTables |
A previously computed set of likelihood functions, to speed up computation for the same hypothesis testing problem. Otherwise, it is computed ab initio, resulting in a longer running time. |
tol |
A numerical tolerance, defaults to 1e-7 |
This essentially computes the probabilities of hitting the boundaries using a recursion.
upper |
The upper boundary that indicates rejection of the null hypothesis |
lower |
The upper boundary that indicates acceptance of the null hypothesis |
estimate |
The estimated α and β values corresponding to the two boundaries |
Balasubramanian Narasimhan
“Sequential Generalized Likelihood Ratio Tests for Vaccine Safety Evaluation” doi: 10.1002/sim.4036.
See Also glrSearch
computeBoundary(b1=2.8, b0=3.3, p=c(.5, .75))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.