plotcorr | R Documentation |

This function plots a correlation matrix using ellipse-shaped glyphs for each entry. The ellipse represents a level curve of the density of a bivariate normal with the matching correlation.

```
plotcorr(corr, outline = TRUE, col = 'grey', numbers = FALSE,
type = c("full","lower","upper"),
diag = (type == "full"), bty = "n", axes = FALSE,
xlab = "", ylab = "", asp = 1,
cex.lab = par("cex.lab"), cex = 0.75*par("cex"),
mar = 0.1 + c(2,2,4,2), ...)
```

`corr` |
A matrix containing entries between |

`outline` |
Whether the ellipses should be outlined in the default colour. |

`col` |
Which colour(s) to use to fill the ellipses. |

`numbers` |
Whether to plot numerical correlations in place of ellipses. If
numbers is |

`type` |
Character. Plot |

`diag` |
Logical. Plot diagonal elements or not. |

`bty, axes, xlab, ylab, asp, mar, cex.lab, ...` |
Graphical parameters
which will be passed to |

`cex` |
Graphical parameter
which will be passed to |

The ellipses being plotted will be tangent to a unit character square,
with the shape chosen to match the required correlation. If `numbers = FALSE`

,
the `col`

vector will be recycled to colour each of the ellipses; if
`TRUE`

, it will be ignored.

Duncan Murdoch; Gregor Gorjanc suggested the `type`

and `diag`

options.

Murdoch, D.J. and Chow, E.D. (1996). A graphical display of large correlation matrices. The American Statistician 50, 178-180. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/2684435")}.

`ellipse`

```
save.par <- par(ask = interactive())
# Plot the correlation matrix for the mtcars data full model fit
data(mtcars)
fit <- lm(mpg ~ ., mtcars)
plotcorr(summary(fit, correlation = TRUE)$correlation)
# Plot a second figure with numbers in place of the
# ellipses
plotcorr(summary(fit, correlation = TRUE)$correlation, numbers = TRUE)
# Colour the ellipses to emphasize the differences. The color range
# is based on RColorBrewer's Reds and Blues (suggested by Gregor Gorjanc)
corr.mtcars <- cor(mtcars)
ord <- order(corr.mtcars[1,])
xc <- corr.mtcars[ord, ord]
colors <- c("#A50F15","#DE2D26","#FB6A4A","#FCAE91","#FEE5D9","white",
"#EFF3FF","#BDD7E7","#6BAED6","#3182BD","#08519C")
plotcorr(xc, col=colors[5*xc + 6])
plotcorr(xc, col=colors[5*xc + 6], type = "upper")
plotcorr(xc, col=colors[5*xc + 6], type = "lower", diag = TRUE)
par(save.par)
```

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