dsm.var.movblk: Variance estimation via parametric moving block bootstrap
In dsm: Density Surface Modelling of Distance Sampling Data

dsm.var.movblk

R Documentation

Variance estimation via parametric moving block bootstrap

Description

This function is deprecated, use dsm_var_movblk.

Usage

dsm.var.movblk(
  dsm.object,
  pred.data,
  n.boot,
  block.size,
  off.set,
  ds.uncertainty = FALSE,
  samp.unit.name = "Transect.Label",
  progress.file = NULL,
  bs.file = NULL,
  bar = TRUE
)

Arguments

`dsm.object`	object returned from `dsm`.
`pred.data`	either: a single prediction grid or list of prediction grids. Each grid should be a `data.frame` with the same columns as the original data.
`n.boot`	number of bootstrap resamples.
`block.size`	number of segments in each block.
`off.set`	a a vector or list of vectors with as many elements as there are in `pred.data`. Each vector is as long as the number of rows in the corresponding element of `pred.data`. These give the area associated with each prediction cell. If a single number is supplied it will be replicated for the length of `pred.data`.
`ds.uncertainty`	incorporate uncertainty in the detection function? See Details, below. Note that this feature is EXPERIMENTAL at the moment.
`samp.unit.name`	name sampling unit to resample (default 'Transect.Label').
`progress.file`	path to a file to be used (usually by Distance) to generate a progress bar (default `NULL` – no file written).
`bs.file`	path to a file to store each bootstrap round. This stores all of the bootstrap results rather than just the summaries, enabling outliers to be detected and removed. (Default `NULL`).
`bar`	should a progress bar be printed to screen? (Default `TRUE`).