oneBsIter: oneBsIter - Computations for one bootstrap iteration
In tmcd82070/Rdistance: Density and Abundance from Distance-Sampling Surveys

oneBsIter

R Documentation

oneBsIter - Computations for one bootstrap iteration

Description

An internal (un-exported) function to perform density and abundance calculations on one iteration of the bootstrap.

Usage

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
)

Arguments

`indexDf`	A data frame containing row indices to use for subsetting the rows of `data`. The actual indices are in column `rowIndex`.
`key`	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"`.
`data`	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`.
`formula`	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.
`likelihood`	String specifying the likelihood to fit. Built-in likelihoods at present are "halfnorm", "hazrate", and "negexp".
`w.lo`	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`.
`w.hi`	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`.
`expansions`	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`).
`series`	If `expansions` > 0, this string specifies the type of expansion to use. Valid values at present are 'simple', 'hermite', and 'cosine'.
`x.scl`	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.
`g.x.scl`	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.
`outputUnits`	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`.
`warn`	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`.
`area`	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.
`propUnitSurveyed`	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`.
`pb`	A progress bar created with `progress::progress_bar$new()`.
`plot.bs`	Logical. Whether to plot bootstrap estimate of detection function. A plot must already exist because this uses `lines`.
`plotCovValues`	Data frame containing values of covariates to plot, if `plot.bs` is TRUE.