logistic.start.limits

Starting values and limits for parameters of the logistic 
distance function.

Distance-sampling analyses estimate density and
abundance of organisms in ecology when detection probability declines with
increasing distance from the observers. Distance-sampling is popular
in most branches of ecology and especially when
organisms are observed from aerial platforms (e.g., airplane or drone),
surface vessels (e.g., boat or truck), or along walking transects.
Rdistance analyzes data collected on both point and line transects,
estimates overall (study area) and site-level (transect or point)
density, and allows users to specify regression-like formula (similar
to lm or glm) for covariates. A large suite of classical,
parametric detection functions are
included along with some uncommon parametric
functions (e.g., Gamma, negative exponential) and non-parametric
smoothed distance functions. Custom (user-defined) detection functions
can be implemented (see vignette).  Measurement unit integrity is
enforced with internal unit conversion when necessary.
The help files and vignettes have been
vetted by multiple authors and tested in workshop
settings.

Trent McDonald

Rdistance

Distance-Sampling Analyses for Density and Abundance Estimation

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

logistic.start.limits function

<dl><dt>dist</dt>
<dd>A numeric vector containing observed distances with measurement
units.</dd>
<dt>covars</dt>
<dd>Data frame containing values of covariates at 
each observation in <code>dist</code>.</dd>
<dt>expansions</dt>
<dd>A scalar specifying the number of terms 
in <code>series</code>. Depending on the series, this could be 0 through 5.
The default of 0 equates to no expansion terms of any type.</dd>
<dt>w.lo</dt>
<dd>Scalar value of the lowest observable distance, with measurement
units. 
This is the left truncation sighting distance. Values less than 
<code>w.lo</code> are allowed in <code>dist</code>, but are ignored and 
their likelihood value is set to
 <code>NA</code> in the output.</dd>
<dt>w.hi</dt>
<dd>Scalar value of the largest observable distance, with measurement
units. 
This is the right truncation sighting distance.
Values greater than <code>w.hi</code> are allowed in <code>dist</code>, 
but are ignored and their likelihood value is 
set to <code>NA</code> in the output.</dd></dl>

Arguments

logistic.start.limits - Start and limit values for logistic distance function — logistic.start.limits

<dl>

<dt>dist</dt>
<dd>A numeric vector containing observed distances with measurement
units.</dd>


<dt>covars</dt>
<dd>Data frame containing values of covariates at 
each observation in <code>dist</code>.</dd>


<dt>expansions</dt>
<dd>A scalar specifying the number of terms 
in <code>series</code>. Depending on the series, this could be 0 through 5.
The default of 0 equates to no expansion terms of any type.</dd>


<dt>w.lo</dt>
<dd>Scalar value of the lowest observable distance, with measurement
units. 
This is the left truncation sighting distance. Values less than 
<code>w.lo</code> are allowed in <code>dist</code>, but are ignored and 
their likelihood value is set to
 <code>NA</code> in the output.</dd>


<dt>w.hi</dt>
<dd>Scalar value of the largest observable distance, with measurement
units. 
This is the right truncation sighting distance.
Values greater than <code>w.hi</code> are allowed in <code>dist</code>, 
but are ignored and their likelihood value is 
set to <code>NA</code> in the output.</dd>

</dl>

logistic.start.limits - Start and limit values for logistic distance function

logistic.start.limits: logistic.start.limits - Start and limit values for logistic distance function

Description

Usage

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Arguments

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