body_condition_measurement_estimates

Posterior estimates for lengths and widths of a whale. See 
<code>help("body_condition")</code> for computation details.

datasets

Implementation of Bayesian models for estimating object lengths and morphological relationships between object lengths using photographic data collected from drones. The Bayesian model is described in "Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from drones" (Bierlich et al., 2021, <doi:10.3354/meps13814>).

K.C. Bierlich

Xcertainty

Estimating Lengths and Uncertainty from Photogrammetric Imagery

Joshua Hewitt

Enrico Pirotta

body_condition_measurement_estimates function

A list with 5 elements:<dl>
 <dt>altimeters</dt>
<dd>Posterior samples and summaries for altimeters</dd> <dt>images</dt>
<dd>Posterior samples and summaries for images</dd> <dt>pixel_error</dt>
<dd>Posterior samples and summaries for pixel error 
 component of measurement error model</dd> <dt>objects</dt>
<dd>Posterior samples and summaries for unknown object lengths 
 that were estimated</dd> <dt>summaries</dt>
<dd><code>data.frame</code>s with posterior summaries, collated from
 all other list elements.</dd>
</dl>

Format

Sample MCMC output — body_condition_measurement_estimates

A list with 5 elements:<dl>
 <dt>altimeters</dt>
<dd>Posterior samples and summaries for altimeters</dd>

 <dt>images</dt>
<dd>Posterior samples and summaries for images</dd>

 <dt>pixel_error</dt>
<dd>Posterior samples and summaries for pixel error 
 component of measurement error model</dd>

 <dt>objects</dt>
<dd>Posterior samples and summaries for unknown object lengths 
 that were estimated</dd>

 <dt>summaries</dt>
<dd><code>data.frame</code>s with posterior summaries, collated from
 all other list elements.</dd>


</dl>

body_condition_measurement_estimates: Sample MCMC output

Description

Usage

Arguments

Format