An internal (un-exported) function to perform density and abundance calculations on one iteration of the bootstrap.
oneBsIter(
indexDf,
key,
data,
formula,
likelihood,
w.lo,
w.hi,
expansions,
series,
x.scl,
g.x.scl,
outputUnits,
warn,
area,
propUnitSurveyed,
pb,
plot.bs,
plotCovValues
)A data frame containing density and abundance and other relevant statistics for one iteration of the bootstrap.
A data frame containing row indices to use
for subsetting the rows of data. The actual indices are
in column rowIndex.
A data frame containing the current id of the
BS iteration. This is included for compatability with
dplyr::group_modify, but it is not used internally.
The original non-resampled data have key == "Original".
An Rdistance nested data frame containing
the data to bootstrap resample. Rows of this data frame,
equating to transects, are sampled using the indicies in
indexDf$rowIndex.
A standard formula object. For example, dist ~ 1,
dist ~ covar1 + covar2). The left-hand side (before ~)
is the name of the vector containing off-transect or radial detection distances.
The right-hand side contains the names of covariate
vectors to fit in the detection
function, and potentially group sizes.
Covariates can be either detection level
or transect level and can appear in data or exist in the
global working environment. Regular R scoping
rules apply.
String specifying the likelihood to fit. Built-in likelihoods at present are "halfnorm", "hazrate", and "negexp".
Lower or left-truncation limit of the distances in distance data.
This is the minimum possible off-transect distance. Default is 0. If
w.lo is greater than 0, it must be assigned measurement units
using units(w.lo) <- "<units>" or
w.lo <- units::set_units(w.lo, "<units>").
See examples in the help for set_units.
Upper or right-truncation limit of the distances
in dist. This is the maximum off-transect distance that
could be observed. If unspecified (i.e., NULL),
right-truncation is set to the maximum of the observed
distances. If w.hi is specified, it must have associated
measurement units. Assign measurement units
using units(w.hi) <- "<units>" or
w.hi <- units::set_units(w.hi, "<units>").
See examples in the help for set_units.
A scalar specifying the number of terms
in series to compute. Depending on the series,
this could be 0 through 5. The default of 0 equates
to no expansion terms of any type. No expansion terms
are allowed (i.e., expansions is forced to 0) if
covariates are present in the detection function
(i.e., right-hand side of formula includes
something other than 1).
If expansions > 0, this string
specifies the type of expansion to use. Valid values at
present are 'simple', 'hermite', and 'cosine'.
The x coordinate (a distance) at which the
detection function will be scaled. g.x.scl can be a distance
or the string "max".
When x.scl is specified (i.e., not 0 or "max"), it must have measurement
units assigned using either library(units);units(x.scl) <- '<units>'
or x.scl <- units::set_units(x.scl, <units>). See
units::valid_udunits() for valid symbolic units.
Height of the distance function at coordinate x.
The distance function
will be scaled so that g(x.scl) = g.x.scl.
If g.x.scl is not
a data frame, it must be a numeric value (vector of length 1)
between 0 and 1.
A string specifying the symbolic measurement
units for results. Valid units are listed in units::valid_udunits().
The strings for common distance symbolic units are:
"m" - meters, "ft" - feet, "cm" - centimeters, "mm" -
millimeters, "mi" - miles, "nmile" -
nautical miles ("nm" is nano meters), "in" - inches,
"yd" - yards, "km" - kilometers, "fathom" - fathoms,
"chains" - chains, and "furlong" - furlongs.
If outputUnits is unspecified (NULL),
output units will be the same as those on
distances in data.
A logical scalar specifying whether to issue
an R warning if the estimation did not converge or if one
or more parameter estimates are at their boundaries.
For estimation, warn should generally be left at
its default value of TRUE. When computing bootstrap
confidence intervals, setting warn = FALSE
turns off annoying warnings when an iteration does
not converge. Regardless of warn, after
completion all messages about
convergence and boundary conditions are printed
by print.dfunc, print.abund, and
plot.dfunc.
A scalar containing the total area of inference. Usually, this is
study area size. If area is NULL (the default),
area will be set to 1 square unit of the output units and density estimates
will be produced.
If area is not NULL, it must have measurement units
assigned by the units package.
The units on area must be convertible
to squared output units. Units
on area must be two-dimensional.
For example, if output units are "foo",
units on area must be convertible to "foo^2" by the units
package. Units of "km^2", "cm^2", "ha", "m^2", "acre", "mi^2", and several
others are acceptable.
A scalar or vector of real numbers between 0 and 1.
The proportion of the default sampling unit that
was surveyed. If both sides of line transects were observed,
propUnitSurveyed
= 1. If only a single side of line transects were observed, set
propUnitSurveyed = 0.5. For point transects, this should be set to
the proportion of each circle that was observed. Length must either be
1 or the total number of transects in x.
A progress bar created with progress::progress_bar$new().
Logical. Whether to plot bootstrap estimate of detection function.
A plot must already exist because this uses lines.
Data frame containing values of covariates to plot,
if plot.bs is TRUE.