genfun: #***see comments at top of genmax for description of the...

Description Usage

Description

#***see comments at top of genmax for description of the first #***arguments of this subroutine #it looks like ti is necessary to sned down the scaled information as well as the scaled and transformed x and y. # # # # #conlev (I) confidence level as a probability (e.g.0.95) # # # #kodef (I but should be O!) range kode for the function to be computed # 1 -infinity to +infinity # 2 greater than zero # 3 between 0 and 1 # # # #fargv(nargv) (I) double precision vector of arguments for the # function (e.g.times for failure probabilities # or probs for quantiles) # # #nargv (I) length of fargv (should be 0 if no argument) # # # #kfuncp (I) function number # x1 failure probability # x2 distribution quantile # x3 hazard rate # >100 user specified # # for more complicated models (e.g., model 1, 2, or 3) # x is the subpopulation number (0 for entire population) # # # # kpopu (I) for mixtures, specifies which population for quantiles # failure probs, etc. # # #kpoint (I) row number for getting explanatory variable conditions # send down kpoint=1 if no regression # # #vcvs(nparm,nparm) (I) double precision covariance matrix of thetas # # #epsxp (I) double precision epsilon for finite differences # if zero is sent down, 1.0d-08 is used (now hardwired) # # #fest(nargv) (O) estimates of function # #stderr(nargv) (O) estimated standard error of fest # #xlow(nargv) (O) lower confidence bounds # #xup(nargv) (O) upper confidence bound

Usage

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GENFUN(
  kmod,
  kdist,
  ilabp,
  ilabd,
  theta,
  thetas,
  kodet,
  ifix,
  nparm,
  npard,
  y,
  ncoly,
  nrownw,
  x,
  ncolx,
  codes,
  weight,
  ty,
  ncolty,
  tcodes,
  kprint,
  kparv,
  nrvar,
  mrelat,
  nrelat,
  mnrvar,
  conlev,
  kodef,
  fargv,
  nargv,
  kfuncp,
  kpopu,
  kpoint,
  vcvs,
  fest,
  std_err,
  xlow,
  xup,
  nxd,
  intd,
  ipxcd,
  irelad,
  ier,
  llog,
  kmodp,
  maxpd,
  nregr,
  kmccde,
  pfail,
  npardm,
  nnum,
  kparm,
  iup,
  nterd
)

Auburngrads/SMRD documentation built on Sept. 14, 2020, 2:21 a.m.