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unmarked for hierarchical modeling of abundance and occurrence. The
function unmarked::formatWide() takes a data frame and converts it to one
of several unmarked objects, which can then be used for modeling. This
function converts data from a format in which each row is an observation
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    <div class="page-header">
    <h1>Format EBD data for occupancy modeling with <code>unmarked</code></h1>
    <small class="dont-index">Source: <a href="https://github.com/CornellLabofOrnithology/auk/blob/HEAD/R/format-unmarked-occu.R" class="external-link"><code>R/format-unmarked-occu.R</code></a></small>
    <div class="hidden name"><code>format_unmarked_occu.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Prepare a data frame of species observations for ingestion into the package
<code>unmarked</code> for hierarchical modeling of abundance and occurrence. The
function <code><a href="https://rbchan.github.io/unmarked/reference/formatWideLong.html" class="external-link">unmarked::formatWide()</a></code> takes a data frame and converts it to one
of several <code>unmarked</code> objects, which can then be used for modeling. This
function converts data from a format in which each row is an observation
(e.g. as in the eBird Basic Dataset) to the esoteric format required by
<code><a href="https://rbchan.github.io/unmarked/reference/formatWideLong.html" class="external-link">unmarked::formatWide()</a></code> in which each row is a site.</p>
    </div>

    <div id="ref-usage">
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">format_unmarked_occu</span><span class="op">(</span></span>
<span>  <span class="va">x</span>,</span>
<span>  site_id <span class="op">=</span> <span class="st">"site"</span>,</span>
<span>  response <span class="op">=</span> <span class="st">"species_observed"</span>,</span>
<span>  <span class="va">site_covs</span>,</span>
<span>  <span class="va">obs_covs</span></span>
<span><span class="op">)</span></span></code></pre></div>
    </div>

    <div id="arguments">
    <h2>Arguments</h2>
    <dl><dt>x</dt>
<dd><p><code>data.frame</code>; observation data, e.g. from the eBird Basic Dataset
(EBD), for <strong>a single species</strong>, that has been filtered to those with
repeat visits by <code><a href="filter_repeat_visits.html">filter_repeat_visits()</a></code>.</p></dd>


<dt>site_id</dt>
<dd><p>character; a unique idenitifer for each "site", typically
identifying observations from a unique location by the same observer
within a period of temporal closure. Data output from
<code><a href="filter_repeat_visits.html">filter_repeat_visits()</a></code> will have a <code>.site_id</code> variable that meets these
requirements.</p></dd>


<dt>response</dt>
<dd><p>character; the variable that will act as the response in
modeling efforts, typically a binary variable indicating presence or
absence or a count of individuals seen.</p></dd>


<dt>site_covs</dt>
<dd><p>character; the variables that will act as site-level
covariates, i.e. covariates that vary at the site level, for example,
latitude/longitude or habitat predictors. If this parameter is missing, it
will be assumed that any variable that is not an observation-level
covariate (<code>obs_covs</code>) or the <code>site_id</code>, is a site-level covariate.</p></dd>


<dt>obs_covs</dt>
<dd><p>character; the variables that will act as observation-level
covariates, i.e. covariates that vary within sites, at the level of
observations, for example, time or length of observation.</p></dd>

</dl></div>
    <div id="value">
    <h2>Value</h2>
    

<p>A data frame that can be processed by <code><a href="https://rbchan.github.io/unmarked/reference/formatWideLong.html" class="external-link">unmarked::formatWide()</a></code>.
Each row will correspond to a unqiue site and, assuming there are a maximum
of <code>N</code> observations per site, columns will be as follows:</p><ol><li><p>The unique site identifier, named "site".</p></li>
<li><p><code>N</code> response columns, one for each observation, named "y.1", ..., "y.N".</p></li>
<li><p>Columns for each of the site-level covariates.</p></li>
<li><p>Groups of <code>N</code> columns of observation-level covariates, one column per
covariate per observation, names "covariate_name.1", ...,
"covariate_name.N".</p></li>
</ol></div>
    <div id="details">
    <h2>Details</h2>
    <p>Hierarchical modeling requires repeat observations at each "site" to
estimate detectability. A "site" is typically defined as a geographic
location visited by the same observer within a period of temporal closure.
To define these sites and filter out observations that do not correspond to
repeat visits, users should use <code><a href="filter_repeat_visits.html">filter_repeat_visits()</a></code>, then pass the
output to this function.</p>
<p><code>format_unmarked_occu()</code> is designed to prepare data to be converted into
an <code>unmarkedFrameOccu</code> object for occupancy modeling with
<code><a href="https://rbchan.github.io/unmarked/reference/occu.html" class="external-link">unmarked::occu()</a></code>; however, it can also be used to prepare data for
conversion to an <code>unmarkedFramePCount</code> object for abundance modeling with
<code><a href="https://rbchan.github.io/unmarked/reference/pcount.html" class="external-link">unmarked::pcount()</a></code>.</p>
    </div>
    <div id="see-also">
    <h2>See also</h2>
    <div class="dont-index"><p>Other modeling: 
<code><a href="filter_repeat_visits.html">filter_repeat_visits</a>()</code></p></div>
    </div>

    <div id="ref-examples">
    <h2>Examples</h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># read and zero-fill the ebd data</span></span></span>
<span class="r-in"><span><span class="va">f_ebd</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.file.html" class="external-link">system.file</a></span><span class="op">(</span><span class="st">"extdata/zerofill-ex_ebd.txt"</span>, package <span class="op">=</span> <span class="st">"auk"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">f_smpl</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/system.file.html" class="external-link">system.file</a></span><span class="op">(</span><span class="st">"extdata/zerofill-ex_sampling.txt"</span>, package <span class="op">=</span> <span class="st">"auk"</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="co"># data must be for a single species</span></span></span>
<span class="r-in"><span><span class="va">ebd_zf</span> <span class="op">&lt;-</span> <span class="fu"><a href="auk_zerofill.html">auk_zerofill</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">f_ebd</span>, sampling_events <span class="op">=</span> <span class="va">f_smpl</span>,</span></span>
<span class="r-in"><span>                       species <span class="op">=</span> <span class="st">"Collared Kingfisher"</span>,</span></span>
<span class="r-in"><span>                       collapse <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="va">occ</span> <span class="op">&lt;-</span> <span class="fu"><a href="filter_repeat_visits.html">filter_repeat_visits</a></span><span class="op">(</span><span class="va">ebd_zf</span>, n_days <span class="op">=</span> <span class="fl">30</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="co"># format for unmarked</span></span></span>
<span class="r-in"><span><span class="co"># typically one would join in habitat covariates prior to this step</span></span></span>
<span class="r-in"><span><span class="va">occ_wide</span> <span class="op">&lt;-</span> <span class="fu">format_unmarked_occu</span><span class="op">(</span><span class="va">occ</span>,</span></span>
<span class="r-in"><span>                                 response <span class="op">=</span> <span class="st">"species_observed"</span>,</span></span>
<span class="r-in"><span>                                 site_covs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"latitude"</span>, <span class="st">"longitude"</span><span class="op">)</span>,</span></span>
<span class="r-in"><span>                                 obs_covs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"effort_distance_km"</span>, </span></span>
<span class="r-in"><span>                                              <span class="st">"duration_minutes"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="co"># create an unmarked object</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/ns-load.html" class="external-link">requireNamespace</a></span><span class="op">(</span><span class="st">"unmarked"</span>, quietly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span>  <span class="va">occ_um</span> <span class="op">&lt;-</span> <span class="fu">unmarked</span><span class="fu">::</span><span class="fu"><a href="https://rbchan.github.io/unmarked/reference/formatWideLong.html" class="external-link">formatWide</a></span><span class="op">(</span><span class="va">occ_wide</span>, type <span class="op">=</span> <span class="st">"unmarkedFrameOccu"</span><span class="op">)</span></span></span>
<span class="r-in"><span>  <span class="fu">unmarked</span><span class="fu">::</span><span class="fu">summary</span><span class="op">(</span><span class="va">occ_um</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> unmarkedFrame Object</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 66 sites</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Maximum number of observations per site: 10 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Mean number of observations per site: 3.8 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Sites with at least one detection: 37 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Tabulation of y observations:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> FALSE  TRUE  &lt;NA&gt; </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   173    78   409 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Site-level covariates:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     latitude       longitude    </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Min.   :1.206   Min.   :103.7  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  1st Qu.:1.303   1st Qu.:103.7  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Median :1.337   Median :103.8  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Mean   :1.334   Mean   :103.8  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  3rd Qu.:1.354   3rd Qu.:103.9  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Max.   :1.446   Max.   :104.0  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Observation-level covariates:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  effort_distance_km duration_minutes</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Min.   : 0.100     Min.   :  1.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  1st Qu.: 0.200     1st Qu.: 15.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Median : 1.000     Median : 30.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Mean   : 1.434     Mean   : 62.97  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  3rd Qu.: 2.000     3rd Qu.: 75.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Max.   :10.000     Max.   :480.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  NA's   :584        NA's   :584     </span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># this function can also be used for abundance modeling</span></span></span>
<span class="r-in"><span><span class="va">abd</span> <span class="op">&lt;-</span> <span class="va">ebd_zf</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span></span>
<span class="r-in"><span>  <span class="co"># convert count to integer, drop records with no count</span></span></span>
<span class="r-in"><span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>observation_count <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/integer.html" class="external-link">as.integer</a></span><span class="op">(</span><span class="va">observation_count</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span></span>
<span class="r-in"><span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">observation_count</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%&gt;%</a></span> </span></span>
<span class="r-in"><span>  <span class="co"># filter to repeated visits</span></span></span>
<span class="r-in"><span>  <span class="fu"><a href="filter_repeat_visits.html">filter_repeat_visits</a></span><span class="op">(</span>n_days <span class="op">=</span> <span class="fl">30</span><span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>There was 1 warning in `dplyr::mutate()`.</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> In argument: `observation_count = as.integer(observation_count)`.</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> Caused by warning:</span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span style="color: #BBBB00;">!</span> NAs introduced by coercion</span>
<span class="r-in"><span><span class="co"># prepare for conversion to unmarkedFramePCount object</span></span></span>
<span class="r-in"><span><span class="va">abd_wide</span> <span class="op">&lt;-</span> <span class="fu">format_unmarked_occu</span><span class="op">(</span><span class="va">abd</span>,</span></span>
<span class="r-in"><span>                                 response <span class="op">=</span> <span class="st">"observation_count"</span>,</span></span>
<span class="r-in"><span>                                 site_covs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"latitude"</span>, <span class="st">"longitude"</span><span class="op">)</span>,</span></span>
<span class="r-in"><span>                                 obs_covs <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"effort_distance_km"</span>, </span></span>
<span class="r-in"><span>                                              <span class="st">"duration_minutes"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="co"># create an unmarked object</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/ns-load.html" class="external-link">requireNamespace</a></span><span class="op">(</span><span class="st">"unmarked"</span>, quietly <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span>  <span class="va">abd_um</span> <span class="op">&lt;-</span> <span class="fu">unmarked</span><span class="fu">::</span><span class="fu"><a href="https://rbchan.github.io/unmarked/reference/formatWideLong.html" class="external-link">formatWide</a></span><span class="op">(</span><span class="va">abd_wide</span>, type <span class="op">=</span> <span class="st">"unmarkedFrameOccu"</span><span class="op">)</span></span></span>
<span class="r-in"><span>  <span class="fu">unmarked</span><span class="fu">::</span><span class="fu">summary</span><span class="op">(</span><span class="va">abd_um</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> unmarkedFrame Object</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 65 sites</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Maximum number of observations per site: 10 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Mean number of observations per site: 3.83 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Sites with at least one detection: 36 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Tabulation of y observations:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    0    1    2    3    4    5    6    7    9   10 &lt;NA&gt; </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  174   33   18    7    5    6    2    1    1    2  401 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Site-level covariates:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     latitude       longitude    </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Min.   :1.206   Min.   :103.7  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  1st Qu.:1.302   1st Qu.:103.7  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Median :1.337   Median :103.8  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Mean   :1.333   Mean   :103.8  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  3rd Qu.:1.352   3rd Qu.:103.9  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Max.   :1.446   Max.   :104.0  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Observation-level covariates:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  effort_distance_km duration_minutes</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Min.   : 0.100     Min.   :  1.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  1st Qu.: 0.200     1st Qu.: 15.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Median : 1.000     Median : 30.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Mean   : 1.475     Mean   : 64.75  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  3rd Qu.: 2.000     3rd Qu.: 75.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  Max.   :10.000     Max.   :480.00  </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  NA's   :573        NA's   :573     </span>
</code></pre></div>
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