Description Usage Arguments Details Value
Learns the shape of the objective function within epsilon.
1 2 |
lines |
a dataframe that contains the constants that define the
line represented by each term in the sum. Created as output from
|
startbox |
a list of boxes and their bounds, possibly the output
from a previous call to |
eps |
a non-negative numeric indicating the tolerance within which you would like to learn the function. Default is 0. |
delE |
a non-negative numeric indicating the width of σ^2_e beyond which the algorithm will stop branching boxes. Default is 0. |
delS |
a non-negative numeric indicating the width of σ^2_s beyond which the algorithm will stop branching boxes. Default is 0. |
M |
a non-negative numeric indicating the size of the buffer between
the highest global lower bound and the upper bound of a given box past
that box will now be branched further. Default is |
maxit |
a positive integer indicating the maximum number of iterations of the algorithm. Default is 10. |
ratio |
a logical indicating if |
lognote |
a string to append to the "log.out" log file to annotate
the purpose of each run of the algorithm. For use in benchmarking computation
time. Default is |
This is the primary function that implements the branch-bound-kill
algorithm described in "Approximately Exact Calculations for Linear
Mixed Models" by Lavine & Hodges (2015). This an interative algorithm
that can require substantial computation time. It is recommended that
the user start with a conservative maxit
and do additional
computations as necessary.
The arguments of this function include five settings to control when to stop branching (subdividing) a box:
when the upper and lower bounds are within eps
of one another.
when the width of σ^2_e is less than delE
.
when the width of σ^2_s is less than delS
.
when the upper bound is more than M
below the highest global
lower bound.
when the number of iterations reaches maxit
.
A list of boxes including their limits in σ^2_e and σ^2_e as well as their bounds. Running this function also results in the creation of a log file called "log.out" containing box counts at every iteration.
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