search for: stat_summary

Hello, This is a pretty simple question, but after spending quite a bit of time looking at "Hmisc" and using Google, I can't find the answer. If I use stat_summary(fun.data="mean_cl_boot") in ggplot to generate 95% confidence intervals, how many bootstrap iterations are preformed by default? Can this be changed? I would at least like to be able to report the number of boot strap interations used to generate the CIs. I haven't been able to find...

...of the figure. My question is: how do I change the scale of the y-axis so that it does not have the range between 0 and 1 but between 0 and 0.1? Many thanks. By the way, I am using ggplot2, and here is my code: ------------------------------- year.plot <- ggplot(d, aes(year, rate)) year.plot + stat_summary(fun.y = "mean", geom = "line") ------------------------------- Best, Shige

...quot;Hiccups.dat", header = TRUE) hiccups<-stack(hiccupsData) names(hiccups)<-c("Hiccups","Intervention") hiccups$Intervention_Factor<-factor(hiccups$Intervention, levels = hiccups$Intervention) line <- ggplot(hiccups, aes(Intervention_Factor, Hiccups)) line + stat_summary(fun.y = mean, geom = "point") + stat_summary(fun.y = mean, geom = "line", aes(group=1),colour = "Red", linetype = "dashed")+ stat_summary(fun.data = mean_cl_boot, geom = "errorbar", width = 0.2) + labs(x = "Intervention", y = "Mean Nu...

...4, sep="")) x <- runif(100) df <- data.frame(f1, f2, x) #df <- df[order(df[,1]), ] df <- ddply(df, ~ f1 + f2, transform, Avg_x = mean(x)) myplot <- ggplot(df, aes(x=reorder(f2, Avg_x), x)) + geom_boxplot() + facet_wrap(~ f1, scale = "free", ncol = 1) + stat_summary(fun.y=mean, geom="point", col = "red") myplot Thanks in advance for any help! Lars. [[alternative HTML version deleted]]

...r those two (the line for "Overall Mean" on the other hand is wanted): library(ggplot2) ddf <- data.frame(x = factor(rep(LETTERS[1:2], 5)), y = rnorm(10)) p <- ggplot(ddf, aes(x = x, y = y)) p + geom_point(aes(colour="Observations", shape="Observations")) + stat_summary(aes(colour = "Means", shape ="Means"), fun.y = mean, fun.ymin = min, fun.ymax = max, geom = "point") + geom_hline(aes(yintercept = mean(y), linetype = "Overall Mean"), show_guide = TRUE) I tried to map the linetype in...

Dear List, I am having trouble setting the transparency of a ribbon in ggplot2 and was wondering if anybody had any suggestions so far i have a plot exactly as i want it and i want to add a ribbon connecting the ymax and ymin, whci i do with the following command m10 + stat_summary(geom="ribbon", fun.ymin="min", fun.ymax="max") However the ribbon is a dark grey and i want to make it much lighter or change the colour. I was wondering if anybody had any ideas? I have kept the code used so far brief as it is quite long, however i can expand if req...

...is connected by a line over time p <- ggplot(dat, aes(x=Day, y=Y, group=ID)) + scale_x_continuous(breaks=sort(unique(dat$Day))) + geom_line(colour=alpha("blue", 5/10)) # Adding mean, 1 sd bounds using crossbar geom is ok. But the same info using ribbon geom doesn't work. p + stat_summary(data=dat.less, aes(group=1), geom="crossbar", fun.data="mean_sdl", mult=1) + stat_summary(data=dat.less, aes(group=1), geom="ribbon", fun.data="mean_sdl", mult=1, fill=alpha("blue", 1/10))

Hi All, Here is the code that I'll be referring to: p <- ggplot(wastran.data, aes(PER_KEY, EVENTS)) (p <- p + facet_grid( pool.short ~ .) + stat_summary(aes(y=EVENTS), fun.y = sum, geom="line") + opts(axis.text.x = theme_text(angle = 90, hjust=1), title="Events (15min.) vs. Time: Facet pool", strip.text.y = theme_text()) ) Now, depending on preceding parameters, the 'pool.short' factor variable in 'wastran.data...

Any help with this problem would be greatly appreciated: I need to produce a custom plot i haven't come across in R. Basically, I want to show means, 1st standard deviation and 5th and 95th percentiles visually, using something resembling a boxplot. Is it possible to completely customize a boxplot so that it shows means as the bar (instead of, not as well as medians), standard deviations at

Hii, I created some boxplots with this commands: x <-read.table(file="test.txt") x$group <- rep(1:8, each=5) boxplot(V3~gruppe, data=x) Now, I will connect the boxplots to each other to the min, max and median values. Can anybody help me how to do it ? greetings, J -- View this message in context: http://www.nabble.com/connecting-boxplots-tp21405459p21405459.html Sent from

...=100)*dt$score + (dt$score>100)*100 The following displays mean score by cohort with 95% CL, facetted by subject, and includes a (blue, dashed) reference line (using geom_abline). library(ggplot2) library(Hmisc) ggp <- ggplot(dt,aes(x=cohort, y=score)) + ylim(0,100) ggp <- ggp + stat_summary(fun.data="mean_cl_normal") ggp <- ggp + geom_abline(aes(slope=0,intercept=mean(score)),color="blue",linetype="dashed") ggp <- ggp + facet_grid(subject~.) ggp The problem is that the reference line (from geom_abline) is the same in all facets (= the grand a...

...mistakenly reordered * scale_hue: now spans full range of hue if it less than 360 degrees * scale_hue: rotated default hue range by 15 degrees to avoid unfortunate red-green contrast in two colour case * show now works with ggplot objects * stat_sum: fixed bug which resulted in dropped aesthetics * stat_summary: now warns when dropping records with missing values * stat_summary: should be a little faster * stat_summary: correctly passes ... arguments on fun.data * theme_bw: corrected justification of axis.text.y * trans: bug fixes to logistic transformation * order aesthetic should work again -- http://...

...mistakenly reordered * scale_hue: now spans full range of hue if it less than 360 degrees * scale_hue: rotated default hue range by 15 degrees to avoid unfortunate red-green contrast in two colour case * show now works with ggplot objects * stat_sum: fixed bug which resulted in dropped aesthetics * stat_summary: now warns when dropping records with missing values * stat_summary: should be a little faster * stat_summary: correctly passes ... arguments on fun.data * theme_bw: corrected justification of axis.text.y * trans: bug fixes to logistic transformation * order aesthetic should work again -- http://...

...caciones, mejor que trabajar directamente con "ggplot". > > Sería así: > >   > > #------------- > > library(ggeasy) > >   > > ggplot(data = AÑOS, aes(x = VARIEDAD, y = rAUDPCor, colour = ANO, > >                         group = ANO)) + > >   stat_summary(fun = mean, geom = "point") + > >   stat_summary(fun = mean, geom = "line") + > >  labs(y  =  'mean rAUDPCor') + > >   labs(x  =  'Variety') + > >   theme_bw() + > > easy_rotate_x_labels( angle = 90) > >   > > #----------...

Hi all, I want to plot the grouped means of some variables. The dependent variables and the grouping factor are stored in different columns. I want to draw a simple line-plot of means, in which the x-axis represents the variables and y-axis represents the means. The means of the groups should be connected by lines. So far, the only function that I could find comes closest to what I'm

...x and y axes named incorrectly (thanks to Dieter Menne for spotting this) * can now pass position objects to qplot * y jitter calculated correctly, and jittered data rescales axis now * removed silly legend from quantile plot * extra arguments not being passed on to geoms/stats * fixed bug in stat_summary when summarising a factor * fixed bugs in stat_summary, geom_ribbon, and coord_trans examples _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

...x and y axes named incorrectly (thanks to Dieter Menne for spotting this) * can now pass position objects to qplot * y jitter calculated correctly, and jittered data rescales axis now * removed silly legend from quantile plot * extra arguments not being passed on to geoms/stats * fixed bug in stat_summary when summarising a factor * fixed bugs in stat_summary, geom_ribbon, and coord_trans examples _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages

Dear Colleagues, In the following simple ggplot2 code: -------------------------------- m <- ggplot(d.fig, aes(time, prob)) m + stat_summary(fun.data = "median_hilow", conf.int = .95, geom = "smooth") + facet_wrap(~ Cohort, nrow=1) + coord_cartesian(ylim = c(0, .03)) -------------------------------- Is there a way to replace the y-axis label from "prob" to "Predicted Probability" and replace the x...

...http://github.com/hadley/ggplot2 ggplot2 0.8.2 (2008-02-23) ---------------------------------------- New features * borders, fortify.map and map_data to make it easier to draw map borders and choropleth maps * cut_interval and cut_number utility functions to discretise continuous variables * stat_summary has reparameterised to make it easier to specify different summary functions. It now has four parameters: fun.y, fun.ymin and fun.ymax; and fun.data. See the documentation for stat_summary for more details Minor improvements * ggfluctuation: default to aspect ratio that produces squares * ggsav...

...http://github.com/hadley/ggplot2 ggplot2 0.8.2 (2008-02-23) ---------------------------------------- New features * borders, fortify.map and map_data to make it easier to draw map borders and choropleth maps * cut_interval and cut_number utility functions to discretise continuous variables * stat_summary has reparameterised to make it easier to specify different summary functions. It now has four parameters: fun.y, fun.ymin and fun.ymax; and fun.data. See the documentation for stat_summary for more details Minor improvements * ggfluctuation: default to aspect ratio that produces squares * ggsav...