estTable {forestinventory} | R Documentation |
estTable
Description
estTable
can be used to compare the results of onephase
to multiphase estimations
(twophase
, threephase
). It restructures the estimation results into a table that can
be used to plot the estimation results and provides the basis for further analysis.
Usage
estTable(
est.list,
sae = FALSE,
add.ci = TRUE,
vartypes = c("variance", "ext_variance", "g_variance")
)
Arguments
est.list |
a |
sae |
an object of type |
add.ci |
|
vartypes |
Specifying the variances that should be included in the estimation table. Has to be specified as a |
Value
estTable
returns a list
of the following components:
-
area:
in case of small area estimations: the name of the small area -
estimate:
the point estimates -
vartype:
the type of variance -
variance:
the variance values -
std:
the standard errors (square root of variance values) -
error:
the estimation errors defined as the ratio between standard error and point estimate -
domain:
indicating if current row belongs to asmallarea
orglobal
estimation -
estimator:
the estimator that that was applied -
method:
the estimation method that was applied -
n2:
terrestrial sample size in entire inventory area -
n1:
first phase sample size in entire inventory area -
n0:
in case ofthreephase
estimations: zero phase sample size in entire inventory area -
n2G:
terrestrial sample size in small area -
n1G:
first phase sample size in small area -
n0G:
in case ofthreephase
estimations: zero phase sample size in small area -
r.squared:
coefficient of determination of regression model -
r.squared_reduced:
in case ofthreephase
estimations: coefficient of determination of reduced regression model -
r.squared_full:
in case ofthreephase
estimations: coefficient of determination of full regression model -
ci_lower:
ifadd.ci=TRUE
: lower confidence limit -
ci_upper:
ifadd.ci=TRUE
: upper confidence limit
Note
An estimation object of class onephase
as input is mandatory
Examples
## run onephase estimation:
op.a <- onephase(formula = tvol~1,
data = grisons,
phase_id = list(phase.col = "phase_id_2p", terrgrid.id = 2),
area = list(sa.col = "smallarea", areas = c("A", "B", "C", "D")))
## run small area twophase estimation:
sae.2p.est <- twophase(formula = tvol ~ mean + stddev + max + q75,
data = grisons,
phase_id = list(phase.col = "phase_id_2p", terrgrid.id = 2),
small_area = list(sa.col = "smallarea", areas = c("A", "B","C", "D"),
unbiased = TRUE))
## run small area threephase estimation:
sae.3p.est <- threephase(formula.s0 = tvol ~ mean,
formula.s1 = tvol ~ mean + stddev + max + q75,
data = grisons,
phase_id = list(phase.col = "phase_id_3p", s1.id = 1, terrgrid.id = 2),
small_area=list(sa.col = "smallarea", areas = c("A", "B", "C", "D"),
unbiased = TRUE))
## create estimation table with confidence intervals:
sae.table<- estTable(est.list = list(op.a, sae.2p.est, sae.3p.est), add.ci=TRUE,
sae = TRUE, vartypes = c("variance", "g_variance", "ext_variance"))
sae.table.df<- as.data.frame(sae.table)