There has recently been a lot of discussion of so-called “visually-weighted regression” plots.

Folk hero Hadley Wickham suggests that such plots would be easy to implement with ggplot2, and so I have attempted to prove him right.

The approach outlined in the following Gist would be easy to apply to any situation in which you have a matrix of replicated predictions or bootstrapped fits from a model — any such a matrix would just take the place of the simYhats object.

*Related*

To

**leave a comment** for the author, please follow the link and comment on his blog:

** is.R()**.

R-bloggers.com offers

**daily e-mail updates** about

R news and

tutorials on topics such as: visualization (

ggplot2,

Boxplots,

maps,

animation), programming (

RStudio,

Sweave,

LaTeX,

SQL,

Eclipse,

git,

hadoop,

Web Scraping) statistics (

regression,

PCA,

time series,

trading) and more...

If you got this far, why not

__subscribe for updates__ from the site? Choose your flavor:

e-mail,

twitter,

RSS, or

facebook...

**Tags:** ggplot2, graphics, MASS, reshape2, rstats