as.svrepdesign rather than directly
  by the user.brrweights(strata, psu, match = NULL, small = c("fail", "split",
"merge"), large = c("split", "merge", "fail"))
jk1weights(psu,fpc=NULL, fpctype=c("population","fraction","correction"))
jknweights(strata,psu, fpc=NULL, fpctype=c("population","fraction","correction"))fpc is coded.brrweights a list with elementsjk1weights and jknweights a data frame of replicate
  weights and the scale and rscale arguments to svrVar.fpc is a vector with one entry per stratum it may not have
  names that differ from the stratum identifiers (it may have no names,
  in which case it must be in the same order as
  unique(strata)). To specify population stratum sizes use
  fpctype="population", to specify sampling fractions use
  fpctype="fraction" and to specify the correction directly use
  fpctype="correction"
  
  In BRR variance estimation each stratum is split in two to give
  half-samples. Balanced replicated weights are needed, where
  observations in two different strata end up in the same half stratum
  as often as in different half-strata.BRR, strictly speaking, is
  defined only when each stratum has exactly
  two PSUs.  A stratum with one PSU can be merged with another such
  stratum, or can be split to appear in both half samples with half
  weight.  The latter approach is appropriate for a PSU that was
  deterministically sampled.
  
  A stratum with more than two PSUs can be split into multiple smaller
  strata each with two PSUs or the PSUs can be merged to give two
  superclusters within the stratum.
  
  When merging small strata or grouping PSUs in large strata the
  match variable is used to sort PSUs before merging, to give
  approximate matching on this variable.hadamard, as.svrepdesign,
  svrVar