Hi Suzan, You can do sort of backtransformation inside of ggplot2 (http://had.co.nz/ggplot2).
library(ggplot2) # Create the base scatterplot with y and x axes transformed by logging, # and then back transformed by exponentiating (base <- qplot(carat, price, data=diamonds) + scale_x_log10() + scale_y_log10() + coord_trans(y="pow10", x="pow10")) base + geom_smooth(method="lm") library(mgcv) base + geom_smooth(method="gam", formula = y ~ s(x, bs="cr")) base + geom_smooth(method="gam", formula = y ~ s(x, bs="cr"), fill="grey50") # cf. qplot(carat, price, data=diamonds) + geom_smooth(method="lm") qplot(carat, price, data=diamonds) + geom_smooth(method="gam", formula = y ~ s(x, bs="cr"), fill="grey50") Regards, Hadley On 6/14/07, Suzan Pool <[EMAIL PROTECTED]> wrote: > My question is related to plot( ) in the mgcv package. Before modelling > the data, a few predictors were transformed to normalize them. > Therefore, the x-axes in the plots show transformed predictor values. > How do I back-transform the predictors so that the plots are easier to > interpret? > > Thanks in advance, > Suzan > > -- > Suzan Pool > Oregon State University > Cooperative Institute for Marine Resources Studies > c/o NOAA Fisheries > 520 Heceta Place > P.O. Box 155 > Hammond, OR 97121 > > [EMAIL PROTECTED] > [EMAIL PROTECTED] > Phone: 503-861-1818 x36 TTY > Voice to TTY: 711 > Fax: 503-861-2589 > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
