MLSIM2: method 2

In Auburngrads/SMRD: Statistical Methods For Reliability Data

Description

nonparametric parametric

Usage

MLSIM2(
  x,
  y,
  cen,
  wt,
  nrow,
  nter,
  ny,
  nty,
  ty,
  tcodes,
  kdist,
  gamthr,
  lfix,
  nparm,
  intcpt,
  escale,
  e,
  maxit,
  kprint,
  dscrat,
  iscrat,
  devian,
  thetah,
  fsder,
  vcv,
  r,
  res,
  fv,
  theta,
  iarray,
  marray,
  wtnew,
  xnew,
  ynew,
  iret,
  retmat,
  numsim,
  numret,
  tspass,
  lrand,
  iersim
)

Details

method 2 simulation—nonparametric sampling/parametric inference

must send down a complete data set

parameter meanings same as in wqm_mlboth except the following:

can get rid of scalars like iervcv,ierfit,xlike,nobs

theta(nparm) true value of theta

thetah(nparm) space for thetahat

iarray(marray) scratch space needed to generate random weights

marray length of scratch space. must be at least equal in length to the number of rows in wt a computationally more efficient method is used if the number is larger than the sum of the weights

wtnew vector for the random weights for the simulation

xnew hold space for x

ynew hold space for y

iret amount of stuff to return

retmat(numret,numsim) matrix to return the results, one result per col

numsim number of simulations to be run

nrowr number of rows being returned in retmat

tspass(33) should be able to eliminate

lrand should be able to eliminate

iersim data space too small

need to send down data space big enough to cover all data situations

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