similar to: adding layers in ggplot2 (data and code included)

How can I reproduce this graph in ggplot2 (regression lines and data point superimposed). Thanks, Juliet filename="http://personality-project.org/r/datasets/heating.txt" heating=read.table(filename,header=TRUE) symb=c(19,25,3,23) colors=c("black","red","green","blue")

Warranty on Accuracy, Precision, Legality, ... of R in Research (These questions may well have been raised.) What is the implied warranty of using R for research & publications, consulting, etc.? Alternately, how does one obtain such a warranty? Your answers will be much appreciated. Perhaps you can point me to some websites which discussed this subject in the past. Thanks & regards

Is there an easy way to make graphs for the following data. I have pretest and posttest scores for men and women. I would like to form a 'titlted segment' plot for the data. That is, make segments joining the scores, with different types of segments for men and women. Example data: menpre <- c(43,42,26,39,60,60,46) menpost <- c(40,41,36,42,54,58,43) womenpre <-

Using this data as an example dat <- read.table(textConnection("Id myvar 12 1 12 2 12 6 34 9 34 4 34 8 65 15 65 23"), header = TRUE) closeAllConnections() how can I create another data set that does not have duplicate entries for 'Id', but the included values are randomly selected from the available ones. Thanks! Juliet

Hi, This is not an R question, but I've seen opinions given on non R topics, so I wanted to give it a try. :) How would one treat a variable that was measured once, but is known to fluctuate a lot? For example, I want to include a hormone in my regression as an explanatory variable. However, this hormone varies in its levels throughout a day. Nevertheless, its levels differ substantially

Hi Group, I have a matrix, and I would like to replace numbers less than 0 by the smallest minimum number. Below is an small matrix, and the loop I used. I would like to get suggestions on the "R way" to do this. Thanks, Juliet # example data set mymat <- structure(c(-0.503183609420937, 0.179063475173256, 0.130473004669938, -1.80825226960127, -0.794910626384209, 1.03857280868547,

Hi, Here are three plots: library(ggplot2) data(diamonds) randind <- sample(nrow(diamonds),1000,replace=FALSE) dsmall <- diamonds[randind,] qplot(carat, data=dsmall, geom="histogram",binwidth=1) qplot(carat, data=dsmall, geom="histogram",binwidth=.1) qplot(carat, data=dsmall, geom="histogram",binwidth=.01) What are ways to put these three plots on a single

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

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

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")+

All, For my understanding, I wanted to see if I can get glmnet predictions using both the predict function and also by multiplying coefficients by the variable matrix. This is not worked out. Could anyone suggest where I am going wrong? I understand that I may not have the mean/intercept correct, but the scaling is also off, which suggests a bigger mistake. Thanks for your help. Juliet Hannah

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, I've been working with R for a couple of years, and I've been able to get most of the things done that I needed (sometimes in a roundabout way). A few experienced statisticians told me that R is best for interactive data analysis, but for large-scale computations, one needs something else. I understand that this all depends on what you are trying to accomplish, and R offers many ways

Hi All, I had posted a question on a similar topic, but I think it was not focused. I am posting a modification that I think better accomplishes this. I hope this is ok, and I apologize if it is not. :) I am looping through variables and running several regressions. I have reason to believe that the data is being duplicated because I have been monitoring the memory use on unix. How can I avoid

With this data x <- c(0,0,1,1,2,2) y <- c(5,6,4,3,2,6) lwr <- y-1 upr <- y+1 xlab <- c("Low","Low","Med","Med","High","High") mydata <- data.frame(x,xlab,y,lwr,upr) I would like to make a dot plot and use lwr and upr as error bars. Above 0=Low. I would like there to be some space between the 5 and the 6 corresponding

Hi, I''m gradually moving my site''s config over to Puppet (still in the testing phases at the moment!). Is there any way of getting/referring to a host''s IP address? I want to set up iptables via Puppet, & can use a template but need to get the IP address into the template somehow. I''m getting my node definitions (& thus classes) from LDAP. I

Hi, Is it possible to have an array as the output of a custom fact? And then to pass it into a template in Puppet? I currently have a fact that looks like this: Facter.add("exports") do setcode do case Facter.hostname when (/thishost/i): [ "/local", "/local2" ] end end end & a template like this: <%

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

Hi Group, Here is some data. p <- runif(1000) # sample data groups <- rep(c(1,2),each=500) #conditioning variable mydata <- cbind(p,groups) n <- length(p) u <- (1:n)/(n + 1) # uniform distribution reference for qqplot logp <- -log(p,base=10) logu <- -log(u,base=10) qqplot(logp,logu) How can I make the above qqplot in lattice and/or ggplot2. The sample is uniform, and I take

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