similar to: ggplot2: geom_smooth and legend

Displaying 6 results from an estimated 6 matches similar to: "ggplot2: geom_smooth and legend"

2012 Oct 04
0
extract fit values from geom_smooth
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),
2017 Sep 07
0
Geom_smooth
> 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
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")+
2023 Aug 12
1
geom_smooth
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 >
2016 Jul 20
4
Geom_smooth
Default level = 0.95. Does this mean +/- 0.025 from estimate? [[alternative HTML version deleted]]
2023 Aug 12
1
geom_smooth
?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))+