corsplom_gg_correlation

data

mapping

smooth.col

smooth.lty

smooth.lwd

smooth.alpha

<p>passed to <code><a rd-options="stats" href="/link/cor?package=metaplot&version=0.7.1&to=stats" data-mini-rdoc="stats::cor">cor</a></code></p>

<p>Default lower panel function for corsplom_data_frame() with <code>gg = TRUE</code>. Plots Pearson correlation coefficient.
corsplom_data_frame() typically supplies smooth aesthetics in case smooth is desired; smooth arguments are defined to
suppress corresponding warnings.</p>

internal

Designs plots in terms of core structure.  See 'example(metaplot)'.
Primary arguments are (unquoted) column names; order and type (numeric or not)
dictate the resulting plot.  Specify any y variables, x variable, any groups variable,
and any conditioning variables to metaplot() to generate density plots, boxplots,
mosaic plots, scatterplots, scatterplot matrices, or conditioned plots. Use multiplot()
to arrange plots in grids. Wherever present, scalar column attributes 'label' and 'guide'
are honored, producing fully annotated plots with minimal effort. Attribute 'guide'
is typically units, but may be encoded() to provide interpretations of categorical
values (see '?encode').  Utility unpack() transforms scalar column attributes to row
values and pack() does the reverse, supporting tool-neutral storage of metadata along
with primary data. The package supports customizable aesthetics such as such as reference
lines, unity lines, smooths, log transformation, and linear fits. The user may choose
between trellis and ggplot output. Compact syntax and integrated metadata promote workflow
scalability.

corsplom_gg_correlation: Correlation GG Function for GG Metaplot Corsplom

Description

Usage

Arguments

See Also