Description Details Author(s) References Examples
For both types of plans the OC is implemented. Using a four step approximation generating intermediate plans the final optimal plan are determined quickly. Details can be found in the reference resp. an upcoming paper by the package author and Prof. Dr. Krumbholz.
Package: | ExLiebeRes |
Type: | Package |
Version: | 1.0 |
Date: | 2012-10-22 |
License: | GPL >= 2 |
For an user the function findOptPlan
is the main interface. For
any usable set of parameters p1, p2, alpha, beta the optimal variable
samplnig plan either
of type Lieberman/Reshnikov (\"LR\") or Bruhn-Suhr/Krumbholz (\"BSK\")
is determinded.
For researchers the underlying OC function and intermediate plans may also be evaluated directly.
Not all possible combinations of parameters give numerically usable
results. The underlying integrals become hard to evaluate if the sample
size gets big (n >= ca 750) or the difference between p1 and p2 very
small. Normally the internal integrate
function just bails out in
these cases.
The paper accompanies a paper written by Wolf Krumbholz and Detlef Steuer (to appear)
Maintainer: steuer@hsu-hh.de
paper to appear
1 | findOptPlan(0.01, 0.06, 0.1, 0.1)
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