GBest.pbar: Estimation Functions

Description

These functions carry out direct, model-assisted, and small area estimation through three different modules: "Green Book", "Model-Assisted", and "Small Area".

Usage

GBest.pbar(
  sumyn = "CONDPROP_ADJ",
  ysum,
  sumyd = NULL,
  esttype = "AREA",
  ratiotype = "PERACRE",
  stratalut,
  uniqueid,
  unitvar,
  strvar = NULL,
  domain
)
MAest.ht(y, N, FIA = TRUE, getweights = FALSE, var_method = "LinHTSRS")
MAest.ps(
  y,
  N,
  x_sample,
  x_pop,
  FIA = TRUE,
  save4testing = FALSE,
  getweights = FALSE,
  var_method = "SRSunconditional"
)
MAest.greg(
  y,
  N,
  x_sample,
  x_pop,
  FIA = TRUE,
  save4testing = TRUE,
  modelselect = FALSE,
  getweights = FALSE,
  var_method = "LinHTSRS"
)
MAest.ratio(
  y,
  N,
  x_sample,
  x_pop,
  FIA = TRUE,
  save4testing = TRUE,
  var_method = "LinHTSRS"
)
MAest.gregEN(
  y,
  N,
  x_sample,
  x_pop,
  FIA = TRUE,
  model = "linear",
  save4testing = TRUE,
  getweights = FALSE,
  var_method = "LinHTSRS"
)
MAest.gregRatio(
  yn,
  yd,
  N,
  area,
  x_sample,
  x_pop,
  FIA = TRUE,
  save4testing = FALSE,
  modelselect = FALSE,
  getweights = FALSE,
  var_method = "LinHTSRS"
)
MAest(
  yn = "CONDPROP_ADJ",
  dat.dom,
  cuniqueid,
  unitlut = NULL,
  pltassgn,
  esttype = "ACRES",
  MAmethod,
  strvar = NULL,
  prednames = NULL,
  yd = NULL,
  ratiotype = "PERACRE",
  N,
  area,
  FIA = TRUE,
  modelselect = FALSE,
  getweights = FALSE,
  var_method = ifelse(MAmethod %in% c("PS"), "SRSunconditional", "LinHTSRS")
)
MAest.dom(
  dom,
  dat,
  cuniqueid,
  unitlut,
  pltassgn,
  esttype,
  MAmethod,
  strvar = NULL,
  prednames = NULL,
  domain,
  N,
  area = NULL,
  response = NULL,
  response_d = NULL,
  FIA = TRUE,
  modelselect = FALSE,
  getweights = FALSE,
  var_method = ifelse(MAmethod %in% c("PS"), "SRSunconditional", "LinHTSRS"),
  quiet = FALSE
)
MAest.unit(
  unit,
  dat,
  cuniqueid,
  unitlut,
  unitvar,
  esttype,
  MAmethod = "HT",
  strvar = NULL,
  prednames = NULL,
  domain,
  response,
  response_d = NULL,
  npixels,
  unitarea = NULL,
  FIA = TRUE,
  modelselect = FALSE,
  getweights = FALSE,
  var_method = ifelse(MAmethod %in% c("PS"), "SRSunconditional", "LinHTSRS"),
  quiet = FALSE
)
PBest.pbar(
  dom.prop,
  uniqueid,
  domain,
  strtype = "post",
  stratalut,
  strunitvars,
  unitvars,
  strvar
)
PBest.pbarRatio(
  dom.prop.n,
  dom.prop.d,
  uniqueid,
  domain,
  attribute,
  strtype = "post",
  stratalut,
  strunitvars,
  unitvars,
  strvar
)
SAest.unit(
  fmla.dom.unit,
  pltdat.dom,
  dunitlut.dom,
  yn,
  SApackage,
  dunitvar,
  predselect.unit,
  prior = NULL
)
SAest.area(
  fmla.dom.area,
  pltdat.area,
  dunitlut.area,
  cuniqueid,
  dunitvar = "DOMAIN",
  predselect.area,
  yn,
  SApackage,
  prior = NULL
)
SAest(
  yn = "CONDPROP_ADJ",
  dat.dom,
  cuniqueid,
  pltassgn,
  dunitlut,
  prednames = NULL,
  dunitvar = "DOMAIN",
  SAmethod = "unit",
  SApackage = "JoSAE",
  yd = NULL,
  ratiotype = "PERACRE",
  largebnd.val = NULL,
  showsteps = FALSE,
  savesteps = FALSE,
  stepfolder = NULL,
  prior = NULL,
  modelselect = TRUE,
  multest = TRUE,
  multest_estimators = NULL,
  bayes = FALSE,
  bayes_opts = NULL,
  save4testing = FALSE
)
SAest.dom(
  dom,
  dat,
  cuniqueid,
  dunitlut,
  pltassgn,
  dunitvar = "DOMAIN",
  SApackage,
  SAmethod,
  prednames = NULL,
  domain,
  response = NULL,
  largebnd.val = NULL,
  showsteps = FALSE,
  savesteps = FALSE,
  stepfolder = NULL,
  prior = NULL,
  modelselect = TRUE,
  multest = TRUE,
  multest_estimators = NULL,
  bayes = FALSE,
  bayes_opts = NULL,
  save4testing = FALSE,
  quiet = FALSE
)
SAest.large(
  largebnd.val,
  dat,
  cuniqueid,
  largebnd.unique,
  dunitlut,
  dunitvar = "DOMAIN",
  SApackage = "JoSAE",
  SAmethod = "unit",
  domain,
  response,
  prednames = NULL,
  showsteps = FALSE,
  savesteps = FALSE,
  stepfolder = NULL,
  prior = NULL,
  modelselect = TRUE,
  multest = TRUE,
  multest_estimators = "all",
  bayes = FALSE,
  bayes_opts = NULL,
  vars2keep = NULL,
  save4testing = FALSE,
  quiet = FALSE
)

Arguments

Value

List object containing estimates produced. If GB or PB estimation, output is directly from FIESTAutils, while outputs for MA or SA will be list objects from packages such as `mase`, `sae`, `hbsae`, or `JoSAE`.

Author

Tracey S. Frescino, Grayson W. White

Details

These functions can carry out estimation with data from a variety of domains, but are designed for USFS FIA data.