This function calculates an estimate of the cumulative distribution function
(CDF) for the proportion (expressed as percent) and the total of a response
variable, where the response variable may be defined for either a discrete
or a continuous resource. Optionally, for a discrete resource, the
size-weighted CDF can be calculated. In addition the standard error of the
estimated CDF and confidence bounds are calculated.
the final adjusted weight (inverse of the sample inclusion
probability) for each site, which is either the weight for a
single-stage sample or the stage two weight for a two-stage sample.
x
x-coordinate for location for each site, which is either the
x-coordinate for a single-stage sample or the stage two
x-coordinate for a two-stage sample. The default is NULL.
y
y-coordinate for location for each site, which is either the
y-coordinate for a single-stage sample or the stage two
y-coordinate for a two-stage sample. The default is NULL.
OPTIONAL ARGUMENTS:
stratum
the stratum for each site. The default is NULL.
cluster
the stage one sampling unit (primary sampling unit or cluster)
code for each site. The default is NULL.
N.cluster
the number of stage one sampling units in the resource, which
is required for calculation of finite and continuous population
correction factors for a two-stage sample. For a stratified sample
this variable must be a vector containing a value for each stratum and
must have the names attribute set to identify the stratum codes. The
default is NULL.
wgt1
the final adjusted stage one weight for each site. The default
is NULL.
x1
the stage one x-coordinate for location for each site. The default
is NULL.
y1
the stage one y-coordinate for location for each site. The default
is NULL.
popsize
the known size of the resource - the total number of sampling
units of a discrete resource or the measure of a continuous resource,
which is required for calculation of finite and continuous population
correction factors for a single-stage sample. This variable is also
used to adjust estimators for the known size of a resource. For a
stratified sample this variable must be a vector containing a value
for each stratum and must have the names attribute set to identify the
stratum codes. The default is NULL.
stage1size
the known size of the stage one sampling units of a two-
stage sample, which is required for calculation of finite and
continuous population correction factors for a two-stage sample and
must have the names attribute set to identify the stage one sampling
unit codes. For a stratified sample, the names attribute must be set
to identify both stratum codes and stage one sampling unit codes using
a convention where the two codes are separated by the # symbol, e.g.,
"Stratum 1#Cluster 1". The default is NULL.
support
the support value for each site - the value one (1) for a
site from a discrete resource or the measure of the sampling unit
associated with a site from a continuous resource, which is required
for calculation of finite and continuous population correction
factors. The default is NULL.
swgt
the size-weight for each site, which is the stage two size-weight
for a two-stage sample. The default is NULL.
swgt1
the stage one size-weight for each site. The default is NULL.
unitsize
the known sum of the size-weights of the resource, which for a
stratified sample must be a vector containing a value for each stratum
and must have the names attribute set to identify the stratum codes.
The default is NULL.
vartype
the choice of variance estimator, where "Local" = local mean
estimator and "SRS" = SRS estimator. The default is "Local".
conf
the confidence level. The default is 95%.
cdfval
the set of values at which the CDF is estimated. If a set of
values is not provided, then the sorted set of unique values of the
response variable is used. The default is NULL.
pctval
the set of values at which percentiles are estimated. The
default set is: {5, 25, 50, 75, 95}.
check.ind
a logical value that indicates whether compatability
checking of the input values is conducted, where TRUE = conduct
compatibility checking and FALSE = do not conduct compatibility
checking. The default is TRUE.
warn.ind
a logical value that indicates whether warning messages were
generated, where TRUE = warning messages were generated and FALSE = warning
messages were not generated. The default is NULL.
warn.df
a data frame for storing warning messages. The default is
NULL.
warn.vec
a vector that contains names of the population type, the
subpopulation, and an indicator. The default is NULL.
VALUE:
A list containing the following components:
CDF
a data frame containing the CDF estimates
Pct
a data frame containing the percentile estimates
SIDE EFFECTS:
None
DETAILS:
This function calculates an estimate of the cumulative distribution function
(CDF) for the proportion (expressed as percent) and the total of a
response variable, where the response variable may be defined for either a
discrete or a continuous resource. Optionally, for a discrete resource, the
size-weighted CDF can be calculated. In addition the standard error of
the estimated CDF and confidence bounds are calculated. The user
can supply the set of values at which the CDF is estimated. For the
CDF of a proportion, the Horvitz-Thompson ratio estimator, i.e., the
ratio of two Horvitz-Thompson estimators, is used to calculate the CDF
estimate. For the CDF of a total, the user can supply the known size of
the resource or the known sum of the size-weights of the resource, as
appropriate. For the CDF of a total when either the size of the
resource or the sum of the size-weights of the resource is provided, the
classic ratio estimator is used to calculate the CDF estimate, where
that estimator is the product of the known value and the Horvitz-Thompson ratio
estimator. For the CDF of a total when neither the size of the
resource nor the sum of the size-weights of the resource is provided, the
Horvitz-Thompson estimator is used to calculate the CDF estimate.
Variance estimates for the estimated CDF are calculated using either the
local mean variance estimator or the simple random sampling (SRS)
variance estimator. The choice of variance estimator is subject to user
control. The local mean variance estimator requires the x-coordinate and
the y-coordinate of each site. The SRS variance estimator uses
the independent random sample approximation to calculate joint inclusion
probabilities. Confidence bounds are calculated using a Normal
distribution multiplier. In addition the function uses the estimated
CDF to calculate percentile estimates. Estimated confidence bounds for
the percentile estimates are calculated. The user can supply the set of values
for which percentiles estimates are desired. Optionally, the user can use the
default set of percentiles. The function can accommodate a stratified sample.
For a stratified sample, separate estimates and standard errors are calculated
for each stratum, which are used to produce estimates and standard errors for
all strata combined. Strata that contain a single value are removed. For a
stratified sample, when either the size of the resource or the sum of the size-
weights of the resource is provided for each stratum, those values are used as
stratum weights for calculating the estimates and standard errors for all
strata combined. For a stratified sample when neither the size of the resource
nor the sum of the size-weights of the resource is provided for each stratum,
estimated values are used as stratum weights for calculating the estimates and
standard errors for all strata combined. The function can accomodate
single-stage and two-stage samples for both stratified and unstratified
sampling designs. Finite population and continuous population correction
factors can be utilized in variance estimation. The function checks for
compatibility of input values and removes missing values.
Diaz-Ramos, S., D.L. Stevens, Jr., and A.R. Olsen. (1996). EMAP
Statistical Methods Manual. EPA/620/R-96/XXX. Corvallis, OR: U.S.
Environmental Protection Agency, Office of Research and Development, National
Health Effects and Environmental Research Laboratory, Western Ecology
Division.
EXAMPLES:
z <- rnorm(100, 10, 1)
wgt <- runif(100, 10, 100)
cdfval <- seq(min(z), max(z), length=20)
cdf.est.fcn(z, wgt, vartype="SRS", cdfval=cdfval)
x <- runif(100)
y <- runif(100)
cdf.est.fcn(z, wgt, x, y, cdfval=cdfval)