bcCI

Calculate bias-corrected confidence intervals for bootstrap data
using methods in Manly textbook.

Distance-sampling (<doi:10.1007/978-3-319-19219-2>)
estimates density and abundance of survey targets (e.g., animals) when
detection probability declines with distance.
Distance-sampling is popular in ecology,
especially when survey targets are observed from aerial platforms (e.g.,
airplane or drone), surface vessels (e.g., boat or truck), or along
walking transects.
Distance-sampling includes line-transect studies that measure observation
distances as the closest approach of the sample route (transect) to the target
(i.e., perpendicular off-transect distance), and point-transect studies that
measure observation distances from stationary observers to
the target (i.e., radial distance).
The routines included here fit smooth (parametric) curves to
histograms of observation distances
and use those functions to compute effective sampling distances, density of
targets in the surveyed area, and abundance
of targets in a surrounding study area. Curve shapes include the
half-normal, hazard rate, and negative exponential functions.
Physical measurement units are required and used throughout to
ensure density is reported correctly. The help files
are extensive and have been vetted by multiple authors.

Trent McDonald

Rdistance

Density and Abundance from Distance-Sampling Surveys

Jason Carlisle

Aidan McDonald

Ryan Nielson

Ben Augustine

James Griswald

Patrick McKann

Lacey Jeroue

Hoffman Abigail

Kleinsausser Michael

Joel Reynolds

Pham Quang

Earl Becker

Aaron Christ

Brook Russelland

Stefan Emmons

Will McDonald

Reid Olson

bcCI function

<dl><dt>x.bs</dt>
<dd>A vector of bootstrap estimates of some quantity.</dd>
<dt>x</dt>
<dd>A scalar of the original estimate of the quantity.</dd>
<dt>ci</dt>
<dd>A scalar of the desired confidence interval 
coverage.</dd></dl>

Arguments

bcCI - Bias corrected bootstraps — bcCI

<dl>

<dt>x.bs</dt>
<dd>A vector of bootstrap estimates of some quantity.</dd>


<dt>x</dt>
<dd>A scalar of the original estimate of the quantity.</dd>


<dt>ci</dt>
<dd>A scalar of the desired confidence interval 
coverage.</dd>

</dl>

bcCI - Bias corrected bootstraps

bcCI: bcCI - Bias corrected bootstraps

Description

Usage

Value

Arguments