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    <h1>Deprecated: Prediction curves for arbitrary functions of posteriors</h1>
    <small class="dont-index">Source: <a href="https://github.com/mjskay/tidybayes/blob/HEAD/R/predict_curve.R" class="external-link"><code>R/predict_curve.R</code></a></small>
    <div class="hidden name"><code>predict_curve.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Deprecated function for generating prediction curves (or a density for a
prediction curve).</p>
    </div>

    <div id="ref-usage">
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">predict_curve</span><span class="op">(</span><span class="va">data</span>, <span class="va">formula</span>, summary <span class="op">=</span> <span class="va">median</span>, <span class="va">...</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">predict_curve_density</span><span class="op">(</span></span>
<span>  <span class="va">data</span>,</span>
<span>  <span class="va">formula</span>,</span>
<span>  summary <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">...</span><span class="op">)</span> <span class="fu"><a href="density_bins.html">density_bins</a></span><span class="op">(</span><span class="va">...</span>, n <span class="op">=</span> <span class="va">n</span><span class="op">)</span>,</span>
<span>  n <span class="op">=</span> <span class="fl">50</span>,</span>
<span>  <span class="va">...</span></span>
<span><span class="op">)</span></span></code></pre></div>
    </div>

    <div id="arguments">
    <h2>Arguments</h2>


<dl><dt id="arg-data">data<a class="anchor" aria-label="anchor" href="#arg-data"></a></dt>
<dd><p>A <code><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a></code>, <code><a href="https://tibble.tidyverse.org/reference/tibble.html" class="external-link">tibble</a></code>, or
<code><a href="https://dplyr.tidyverse.org/reference/grouped_df.html" class="external-link">grouped_df</a></code> representing posteriors from a Bayesian model as
might be obtained through <code><a href="spread_draws.html">spread_draws()</a></code>. Grouped data frames
as returned by <a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a> are supported.</p></dd>


<dt id="arg-formula">formula<a class="anchor" aria-label="anchor" href="#arg-formula"></a></dt>
<dd><p>A formula specifying the prediction curve. The left-hand side
of the formula should be a name representing the name of the column that
will hold the predicted response in the returned data frame. The right-hand
side is an expression that may include numeric columns from <code>data</code> and
variables passed into this function in <code>...</code>.</p></dd>


<dt id="arg-summary">summary<a class="anchor" aria-label="anchor" href="#arg-summary"></a></dt>
<dd><p>The function to apply to summarize each predicted response.
Useful functions (if you just want a curve) might be <code><a href="https://rdrr.io/r/stats/median.html" class="external-link">median()</a></code>,
<code><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean()</a></code>, or <code><a href="http://mjskay.github.io/ggdist/reference/point_interval.html" class="external-link">Mode()</a></code>. If you want predictive distribution
at each point on the curve, try <code><a href="density_bins.html">density_bins()</a></code> or
<code><a href="density_bins.html">histogram_bins()</a></code>.</p></dd>


<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
<dd><p>Variables defining the curve. The right-hand side of
<code>formula</code> is evaluated for every combination of values of variables in
<code>...</code>.</p></dd>


<dt id="arg-n">n<a class="anchor" aria-label="anchor" href="#arg-n"></a></dt>
<dd><p>For <code>predict_curve_density</code>, the number of bins to use to
represent the distribution at each point on the curve.</p></dd>

</dl></div>
    <div id="value">
    <h2>Value</h2>
    <p>If <code>formula</code> is in the form <code>lhs ~ rhs</code> and <code>summary</code>
is a function that returns a single value, such as <code>median</code> or
<code>mode</code>, then <code>predict_curve</code> returns a <code>data.frame</code> with a
column for each group in <code>data</code> (if it was grouped), a column for each
variable in <code>...</code>, and a column named <code>lhs</code> with the value of
<code>summary(rhs)</code> evaluated for every group in <code>data</code> and combination
of variables in <code>...</code>.</p>
<p>If <code>summary</code> is a function that returns a <code>data.frame</code>, such as
<code><a href="density_bins.html">density_bins()</a></code>, <code>predict_curve</code> has the same set of columns
as above, except that in place of the <code>lhs</code> column is a set of columns
named <code>lhs.x</code> for every column named <code>x</code> returned by
<code>summary</code>. For example, <code><a href="density_bins.html">density_bins()</a></code> returns a data frame
with the columns <code>mid</code>, <code>lower</code>, <code>upper</code>, and <code>density</code>,
so the data frame returned by <code>predict_curve</code> with <code>summary = density_bins</code> will have columns <code>lhs.mid</code>, <code>lhs.lower</code>,
<code>lhs.upper</code>, and <code>lhs.density</code> in place of <code>lhs</code>.</p>
    </div>
    <div id="details">
    <h2>Details</h2>
    <p><strong>This function is deprecated.</strong> Use <code><a href="https://modelr.tidyverse.org/reference/data_grid.html" class="external-link">modelr::data_grid()</a></code> combined
with <code><a href="http://mjskay.github.io/ggdist/reference/point_interval.html" class="external-link">point_interval()</a></code> or <code><a href="https://dplyr.tidyverse.org/reference/do.html" class="external-link">dplyr::do()</a></code> and
<code><a href="density_bins.html">density_bins()</a></code> instead.</p>
<p>The function generates a predictive curve given posterior draws
(<code>data</code>), an expression (<code>formula</code>), and a set of variables
defining the curve (<code>...</code>). For every group in <code>data</code> (if it is a
grouped data frame—see <a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by()</a>; otherwise the entire data
frame is taken at once), and for each combination of values in <code>...</code>,
the right-hand side of <code>formula</code> is evaluated and its results passed to
the <code>summary</code> function. This allows a predictive curve to be generated,
given (e.g.) some samples of coefficients in <code>data</code> and a set of
predictors defining the space of the curve in <code>...</code>.</p>
<p>Given a summary function like <code><a href="https://rdrr.io/r/stats/median.html" class="external-link">median()</a></code> or <code><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean()</a></code>,
this function will produce the median (resp. mean) prediction at each point
on the curve.</p>
<p>Given a summary function like <code><a href="density_bins.html">density_bins()</a></code>, this function will
produce a predictive distribution for each point on the curve.
<code>predict_curve_density</code> is a shorthand for such a call, with a
convenient argument for adjusting the number of bins per point on the
curve.</p>
    </div>
    <div id="see-also">
    <h2>See also</h2>
    <div class="dont-index"><p>See <code><a href="density_bins.html">density_bins()</a></code>.</p></div>
    </div>
    <div id="author">
    <h2>Author</h2>
    <p>Matthew Kay</p>
    </div>

    <div id="ref-examples">
    <h2>Examples</h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># Deprecated; see examples for density_bins</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"></span>
</code></pre></div>
    </div>
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