similar to: ggplot2: geom_smooth and legend

Dear all, I have a plot with two gaussian distributions: ggplot( tofdf, aes( x = tof, y = counts ) ) + geom_histogram( stat = "identity", position = "stack", fill = 2 ) + geom_smooth( method = "nls", formula = y ~ (a/b)*exp(-(x-c)^2/(2*b^2)) + (d/e)*exp(-(x-f)^2/(2*e^2)), se=F, start=list(a=100, b=1, c=695, d=100, e=1, f=710),

> On Jul 20, 2016, at 10:01 AM, Tom Subia <tgs77m at gmail.com> wrote: > > Default level = 0.95. > Does this mean +/- 0.025 from estimate? > > [[alternative HTML version deleted]] I would have guessed that it meant something along the lines of localized (or one might say "loess-ized") mean +/- 2* similarly localized standard error of the estimate. To find out

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")+

G'day Thomas, On Sat, 12 Aug 2023 04:17:42 +0000 (UTC) Thomas Subia via R-help <r-help at r-project.org> wrote: > Here is my reproducible code for a graph using geom_smooth The call "library(tidyverse)" was missing. :) > I'd like to add a black boundary around the shaded area. I suspect > this can be done with geom_ribbon but I cannot figure this out. Some >

Default level = 0.95. Does this mean +/- 0.025 from estimate? [[alternative HTML version deleted]]

?s 05:17 de 12/08/2023, Thomas Subia via R-help escreveu: > 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))+

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*sqrt(y))) , method = "lm" , formula = y ~ x +

Hi! This is probably completely off base, but your ymin and y max setup lines are different. One uses 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