findmu.Rd
A function that computes the equidistant means muy
and muz
for
a specific mux
. The VUS as well as the set of standard errors are
given as arguments to the function.
findmu(mux = 0, sdx = 1, sdy = 1, sdz = 1, VUS = 1/6, step = 0.001)
The numeric mean of the healthy class. Default is zero.
The numeric standard errors of the healthy, intermediate and diseased class, for which the according means have to be determined given a specifiv VUS.
The Volume Under the Surface. A numeric value between 1/6 and 1. Default is 1/6.
A numeric indicating the step size each iteration takes in order to find the closest set of means. Default set to 0.001.
A data frame with the following components:
The initial mean of the healthy class
The mean of the intermediate class computed for the specified VUS
.
The mean of the diseased class computed for the specified VUS
.
The VUS computed for mux
, muy
and muz
.
Defaults are: VUS = 1/6, standard errors for all three classes equal
1. The searching algorithm is stepwise increasing the differences
muy-mux
and muz-mux
according to the variable step
.
The algorithm stops when the computed VUS exceeds the preferred VUS. The
according parameters mux, muy, muz
are returned with the computed
VUS.
Remark: The bigger VUS
and the smaller step
is chosen, the
longer the computation lasts.
# find equidistant means with mux=2.7 and VUS = 0.45:
findmu(mux = 2.7, VUS = 0.45)
#> Par Coeff
#> 1 mux 2.7000000
#> 2 muy 2.6230000
#> 3 muz 5.2460000
#> 4 VUS 0.4500725
# specify standard errors:
findmu(mux = 2.7, sdx = 1.1, sdy = 1.3, sdz = 1.5, VUS = 0.45)
#> Par Coeff
#> 1 mux 2.7000000
#> 2 muy 2.7840000
#> 3 muz 5.5680000
#> 4 VUS 0.4501836