CueCountingExample

CueCountingExample_units

Cues are treated as an indirect count, requiring the use of multipliers.

datasets

A simple way of fitting detection functions to distance sampling
data for both line and point transects. Adjustment term selection, left and
right truncation as well as monotonicity constraints and binning are
supported. Abundance and density estimates can also be calculated (via a
Horvitz-Thompson-like estimator) if survey area information is provided. See
Miller et al. (2019) <doi:10.18637/jss.v089.i01> for more information on
methods and <https://distancesampling.org/resources/vignettes.html> for example analyses.

Laura Marshall

Distance

Distance Sampling Detection Function and Abundance Estimation

David Miller

T.J. Clark-Wolf

Len Thomas

Jeff Laake

Eric Rexstad

CueCountingExample function

A <code>data.frame</code> with 109 rows and 15 variables.<ul>
<li>`Region.Label stratum labels</li>
<li><code>Area</code> size (km^2) of each stratum</li>
<li><code>Sample.Label</code> transect labels</li>
<li><code>Cue.rate</code> rate of blows per animal per hour</li>
<li><code>Cue.rate.SE</code> variability in cue rate</li>
<li><code>Cue.rate.df</code> degrees of freedom (number of animals sampled for cues)</li>
<li><code>object</code> object ID</li>
<li><code>distance</code> perpendicular distance (km)</li>
<li><code>Sample.Fraction</code> proportion of full circle scanned (radians)</li>
<li><code>Sample.Fraction.SE</code> variability in sampling fraction (0)</li>
<li><code>Search.time</code> Duration of scanning effort (hr)</li>
<li><code>bss</code> Beaufort sea state</li>
<li><code>sp</code> Species detected (all observations W in these data)</li>
<li><code>size</code> Number of animals in group (all 1 in these data)</li>
<li><code>Study.Area</code> study area name</li>
</ul>

Format

Cue counts of whale blows — CueCountingExample

Cue counts of whale blows

CueCountingExample: Cue counts of whale blows

Description

Arguments

Format

Details