search for: after_stat

Displaying 5 results from an estimated 5 matches for "after_stat".

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2024 Aug 11
1
geom_smooth with sd
Dear community Using after_stat() I was able to visualise ggplot with standard deviations instead of a confidence interval as seen in the R help. p1<-ggplot(data = MS1, aes(x= Jahr, y= QI_A,color=Bio, linetype=Bio)) + geom_smooth(aes(fill=Bio, ymax=after_stat(y+se*sqrt(length(y))), ymin=after_stat(y-se*sq...
2024 Aug 11
1
geom_smooth with sd
...ses sqrt(y), while the second uses sqrt(length(y)). Could that play a part, please? Thank you Erin Hodgess, PhD mailto: erinm.hodgess at gmail.com On Sun, Aug 11, 2024 at 10:10?AM SIBYLLE ST?CKLI via R-help < r-help at r-project.org> wrote: > Dear community > > > > Using after_stat() I was able to visualise ggplot with standard deviations > instead of a confidence interval as seen in the R help. > > > > p1<-ggplot(data = MS1, aes(x= Jahr, y= QI_A,color=Bio, linetype=Bio)) + > > geom_smooth(aes(fill=Bio, > ymax=after_stat(y+se*sqrt(le...
2023 Jan 12
1
Reg: ggplot error
...ody would like to go through your whole code. 1. data seems to be read correctly ICUData <- read.csv(file = "ICUData.csv", stringsAsFactors = TRUE) ICUData.neuro <- ICUData[ICUData$surgery == "neuro",] 2. ggplot(ICUData, aes(x=ICUData.neuro$LOS)) + geom_histogram(aes(y=after_stat(density)), binwidth = 5, fill = "darkgrey") gives me error Error in `check_aesthetics()`: ! Aesthetics must be either length 1 or the same as the data (500): x Run `]8;;rstudio:run:rlang::last_error()rlang::last_error()]8;;` to see where the error occurred. which, I b...
2023 Aug 12
1
geom_smooth
...ribbon but I cannot figure this out. Some > advice would be welcome. This works for me: ggplot(scatter_data,aes(x=x_var,y=y_var,))+ geom_point()+ geom_smooth(se=TRUE,fill="blue",color="black",linetype="dashed") + geom_ribbon(stat="smooth", aes(ymin=after_stat(ymin), ymax=after_stat(ymax)), fill=NA, color="black")+ theme_cowplot() Cheers, Berwin
2023 Aug 12
2
geom_smooth
Colleagues, Here is my reproducible code for a graph using geom_smooth set.seed(55) scatter_data <- tibble(x_var = runif(100, min = 0, max = 25) ?????????????????????? ,y_var = log2(x_var) + rnorm(100)) library(ggplot2) library(cowplot) ggplot(scatter_data,aes(x=x_var,y=y_var))+ ? geom_point()+ ? geom_smooth(se=TRUE,fill="blue",color="black",linetype="dashed")+