bootstrap
and other resampling functions
resampMakeFunc(...) resampMakeFuncSimple(...) resampMakeFuncWeighted(...) resampMakeFuncErrF(...) resampMakeFuncErrXY(...) resampMakeFuncBootPred(...) resampMakeFuncCrossVal(...) resampMakeLabel(...) resampMakeNames(...) resampMakeArgument(...) resampMakeWeightsRecip(...) # In all cases, see the actual function for the argument list.
These are not intended to be called directly, but rather by , , and other resampling functions.
If you are interested in using these functions, see the functions themselves for the argument lists, documentation comments at the beginning of the function, and look inside , , and other resampling functions for examples of how to call these functions. But these functions are subject to change without notice.
resampMakeFunc
,
resampMakeFuncSimple
and
resampMakeFuncWeighted
create
functions which are called in a loop to evaluate a specified statistic
given random indices and other arguments.
resampMakeLabel
creates a default label to be used as the main title
when plotting, based on the method used (e.g.
"bootstrap"
) and names of the
data
and
statistic
.
resampMakeNames
either extracts names from a statistic or creates
names; these are used as column names for the
replicates
component
of
"resample"
objects.
resampMakeArgument
is used to evaluate an argument. For example
in
bootstrap(data=df,...,group=a>b)
, where
df
is a data frame,
a
and
b
could be variables in
df
,
be defined inside a function calling
bootstrap
, or
be in a permanent database;
resampMakeArgument
searches in that
order.
resampMakeWeights
constructs importance sampling weights (actually the
reciprocal of those weights) for bootstrap objects. It is called by
addSamples.bootstrap
.