search for: geom_smooths

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")+

Hi all, Is that possible to remove the grey colour in the legend key that goes with the geom_smooth? In my case it doesn't ease the reading of the legend. http://www.4shared.com/file/125864977/e10644f8/desorb.html Cordialement / Regards ------------------------------------------- Benoit Boulinguiez Ecole de Chimie de Rennes (ENSCR) Bureau 1.20 Equipe CIP UMR CNRS 6226 "Sciences

Hi When I run my script using ggplot and geom_smooth I get messages that I would like to suppress: p <- ggplot(dataSubset) p <- p + aes(x = as.Date(factor(key),format="%Y%m%d")) + geom_line() p <- p + geom_smooth(span=0.2,se=FALSE,size=0.7) The messages look like this: geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method

?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))+

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 >

Hi R - listers, I am receiving an error. Does anyone know what this means? J ggplot(subset(foo, Rayos != "Rayos.NA"), aes(x=HTL, y=DevelopIndex, colour=TotalEggs)) +geom_point() +geom_jitter() + facet_grid(Aeventexhumed ~ Rayos) + geom_smooth(method="lm", fill=NA) + ylim(c(0, 7)) Error in +geom_smooth(method = "lm", fill = NA) : invalid argument to unary

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

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

Here is some sample data: mydata <- read.table(textConnection("Est Group Tri 0 0 4.639644 1 0 4.579189 2 0 4.590714 0 1 4.443696 1 1 4.588243 2 1 4.650505 0 2 4.296608 1 2 4.826036 2 2 4.765386"),header=TRUE); closeAllConnections(); I can form two plots,

Hello, I's still working with my tsibble of weight data for the last 20 years. In addition to drawing an overall trend line, using lm, for the whole data set, I'd like to draw short lines that would recompute lm and draw it, say, just for the years from 2010:2015. Here's a short example that I think illustrates what I'm trying to do. The commented out sections show what

Dear Helpers, I wonder whether you might be able to help me. I have a plot composed of ggplot (and a follow on geom_smooth call). I would like to restrict the display range of the y axis to a smaller range, a sort of zooming onto a region. I attempted to use ylim, but it will effect the range (i.e. effect the geom_smooth call). Is there any way that I can save the results up to geom_smooth call

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

Yep, that did it. I didn't know that you could have pipelines within pipelines. Thanks, again, for all your help. -Kevin On 5/16/23 11:44, Rui Barradas wrote: > ?s 15:29 de 16/05/2023, Kevin Zembower via R-help escreveu: >> Hello, >> >> I's still working with my tsibble of weight data for the last 20 years. >> In addition to drawing an overall trend line,

My question is related to plot( ) in the mgcv package. Before modelling the data, a few predictors were transformed to normalize them. Therefore, the x-axes in the plots show transformed predictor values. How do I back-transform the predictors so that the plots are easier to interpret? Thanks in advance, Suzan -- Suzan Pool Oregon State University Cooperative Institute for Marine

Can anyone illuminate the following for me? How can I get rid of the blue line in the key in the second plot? ## Create a simple data frame df=data.frame(x=1:1000, y=2*1:1000+rnorm(1000,sd=1000), type=sample(letters[1:2],1000, replace=TRUE)) ## Very nice! Almost what I want qplot(x, y, data=df, colour=factor(type)) + geom_smooth() ## Make a nicer plot, with smaller points ## but why

With ggplot2, I can plot the glm stat_smooth for binomial data when the response is binary or a two-level factor as follows: data("Donner", package="vcdExtra") ggplot(Donner, aes(age, survived)) + geom_point(position = position_jitter(height = 0.02, width = 0)) + stat_smooth(method = "glm", family = binomial, formula = y ~ x, alpha = 0.2, size=2) But how can I

Hello, I'm trying to create a line graph with a legend, but have no success controlling the legend. Since nothing I've tried seems to work, I must be doing something systematically wrong. Can anyone point this out to me? Here's my data: > weights # A tibble: 1,246 ? 3 Date J K <date> <dbl> <dbl> 1 2000-02-13 133 188 2

Kevin, Maybe also look at what air quality monitoring is being done in area. https://cran.r-project.org/web/packages/RAQSAPI/vignettes/RAQSAPIvignette.html Depends what and how near, but might be something relevant there? Karl Dr Karl Ropkins Transport Studies | Environment | University of Leeds ------------------------------ Message: 2 Date: Tue, 12 Dec 2023 07:52:59 -0800 From: Bert Gunter