Prof Brian Ripley ?????: > On Sun, 19 Feb 2006, Evgeniy Kachalin wrote: > >> Hello, dear R users. >> >> What is the easiest and the most visualli understandable way to analize >> dependency of numerical variable on two factors? > > interaction.plot() is a good start. > >> Is the >> boxplot(y~f1+f2) the good way? It seems that this formula does not work. > > No, nor is it documented to: the help page is there to help you. You > need a single factor as the grouping, so make one via an interaction. > boxplot(y ~ f1:f2) should work. E.g. > > library(MASS) > boxplot(FL ~ sex:sp, data=crabs) Does not work: Îøèáêà â if (any(out[nna])) stats[c(1, 5)] <- range(x[!out], na.rm = TRUE) : ïðîïóùåííîå çíà÷åíèå, à íóæíî TRUE/FALSE Âäîáàâîê: Warning messages: 1: + not meaningful for factors in: Ops.factor(x[floor(d)], x[ceiling(d)]) 2: < not meaningful for factors in: Ops.factor(x, (stats[2] - coef * iqr)) 3: > not meaningful for factors in: Ops.factor(x, (stats[4] + coef * iqr))
Hm... > Another idea is to use lattice's bwplot. E.g. > > library(lattice) > bwplot(FL ~ sex | sp, data=crabs) > > That's not the point. The scales may differ significantly, also this is not conviniet for many factors. ______________________________________________ [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
