Arguments
data
array of data, if a 2D array then each row is considered as 
                one multivariate observation
statistic
function, when sim is set to parametric, 
                     the first argument to statistic must be the data. For 
                     each replicate a simulated dataset returned by ran.gen 
                     will be passed. In all other cases, 
R
number of bootstrap replicates
sim
string, indicates the type of simulation. The default value is 
               "ordinary". Other possible values are parametric, balanced,
               permutation, and antithetic. Importance resampling is 
               specified by including impor
stype
string, indicates what the second argument of statistic 
                 represents. The default value is i for indices. Other 
                 possible values are f for frequencies and w for weights.
                 It is not used when sim is set t
strata
vector of integer, specifies the strata for multi-sample 
                  problems. This may be specified for any simulation, but is 
                  ignored when sim is set to parametric. When strata is 
                  supplied for a nonparamet
L
vector of influence values evaluated at the observations. This is
             used only when sim is set to antithetic. If not supplied, they
             are calculated through a call to empinf.  This will use the 
             infinitesimal jackknife
m
the number of predictions which are to be made at each bootstrap
             replicate. This is most useful for (generalized) linear models. 
             This can only be used when sim is ordinary. m will usually be 
             a single integer but
weights
array of importance weights. If a vector then it should 
                   have as many elements as there are observations in the 
                   input data. When simulation from more than one set of 
                   weights is required, weight
ran.gen
function, used only when sim is set to parametric. It 
                   describes how random values are to be generated. It should
                   be a function of two arguments. The first argument should 
                   be the observed data a
mle
secong argument to ran.gen, typically these will be maximum 
               likelihood estimates of the parameters. For efficiency mle is 
               often a list containing all of the objects needed by ran.gen 
               which can be calculat
simple
boolean, can only be set to TRUE if sim is set to 
                  ordinary, stype is set to I and n is set to 0. Otherwise
                  it is ignored and generates a warning. By default a n by R 
                  index array is created which c
...
other named arguments for statistic which are passed unchanged
               each time.