similar to: abline for intercept-only simple lm models (with and without offset)

Dear All, Let have 10 pair of observations, as shown below. ###################### x <- 1:10 y <- c(1,3,2,4,5,10,13,15,19,22) plot(x,y) ###################### Two fitted? models, with ranges of [1,5] and [5,10],?can be easily fitted separately by lm function as shown below: ####################### mod1 <- lm(y[1:5] ~ x[1:5]) mod2 <- lm(y[5:10] ~ x[5:10]) #######################

Hi Dears, When I introduce an interaciton in a piecewise model I obtain some quite unusual results. If that would't take u such a problem I'd really appreciate an advise from you. I've reproduced an example below... Many thanks x<-rnorm(1000) y<-exp(-x)+rnorm(1000) plot(x,y) abline(v=-1,col=2,lty=2) mod<-lm(y~x+x*(x>-1)) summary(mod) yy<-predict(mod)

Hello fellow R-users,   I’m stuck with something i think is pretty stupid, but i can’t find out where i’m wrong, and it’s turning me crazy!   I am doing a very simple linear regression with Northing/Easting data, then I plot the data as well as the regression line :   > plot(x=Dataset$EASTING, y=Dataset$NORTHING) > fit <- lm(formula = NORTHING ~ EASTING, data = Dataset) > abline(fit)

Dear List, I ran a regression model using lm and produced a regression line using abline. The line ranges from -20 to 20 in x axis, and the section I only want is from -20 to 0. Please kindly advise any function in abline () to set the range of x axes. Thank you Elaine [[alternative HTML version deleted]]

Hello, I'm trying to plot a fitted lm() line on a plot when the one explanatory variable is log transformed and log="x". I get different lines using abline and predict.lm(). #Example x <- 1:100 y <- rnorm(100) plot(y ~ x, log="x") abline(lm(y ~ log(x))) lines(x, predict(lm(y ~ log(x))), lwd=2) I'm sure I'm missing something but could someone tell me which

Hi, when I run > plot.default(z1, z2, xlab = "x", ylab = "y", main = "xxxx", pch = "+") > abline(lm(z1 ~ z2)) then the plot is plotted perfectly (scatterplot), however, the lm() function doesnt appear on the plot. What could be wrong? (Yesterday it worked perfectly, with the lm() line.) Running R 2 on OS X. Mathias Hunsk??r Furevik Norway

Hello all, R2.1.1, Wk2 I am doing some two-step plotting, first using plot() to illustrate the datapoints and then using abline() to place a trend line from a fitted model into the plot. Everything works well as long as the formula of the fitted model i of the type: m1 <- lm(Dependent ~ Independent) then abline(m1) puts the proper straight line into the plot. But if I use: m2 <-

L.S. Since some time there is a new r-project.org site as announced here: https://stat.ethz.ch/pipermail/r-announce/2015/000581.html The logo has changed on the site, but I fail to find a vector graphics file. For the previous logo I used to go to https://svn.r-project.org/R-dev-web/trunk/Logo/ Is there anything similar for the new logo? Many thanks in advance. Kind regards, Tobias --

Full_Name: Tobias Verbeke Version: 2.1.0 OS: GNU/Linux Submission from: (NULL) (81.247.252.229) Would it be possible to use a non-ambiguous example of expressing a day according to the ISO 8601 international standard in the first sentence of the Note section of ?strptime, e.g. "2001-04-18" instead of "2001-02-03" ? Yours, Tobias

Hallo, does a package for Matlab exist in R? If yes, where can I find it and how can I install it under R? Thanks, Corinna

Hi I just realized that when I use linear regression to draw a line through my data points with something like the following: abline(lm(y ~ x)) the length of the line is infinite, i.e., the line goes beyond the smallest and the largest data values. This seems not very right to me (not to mention it looks unaesthetic). I do not mean to imply that the straight-line behavior of my system is

mac osx 10.5.4 R 2.7.1 I have fit a model d<-lm(y~x) with an R^2 of 0.963 but when I issue the command abline(d) the line is below where it ought to be. Looks like the right slope, but not the right intercept. thanks -- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large

L.S. In this bug report https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=14493#c1 it is mentioned that after moving an R installation one should regenerate the Rscript executable. Is there an easy way to do so (after an R installation has been moved)? I have not found any information in the R installation and administration manual. Many thanks in advance for any pointer. Best wishes,

Many thanks, Duncan. We will check the prerelease versions of R 3.2.1. Best regards, Tobias ----- Original Message ----- > From: "Duncan Murdoch" <murdoch.duncan at gmail.com> > To: "Tobias Verbeke" <tobias.verbeke at openanalytics.eu>, "r-devel at r-project.org" <r-devel at r-project.org> > Sent: Saturday, June 6, 2015 2:37:04 PM >

Hi, I am trying to use piecewise linear regression to approximate a nonlinear function. Actually, I don't know how many linear functions I need, therefore, I want build an array of regression models to automate the approximation job. Could you please give me any clue? Attached is ongoing code: rawData = scan("c:/zyang/mass/data/A01/1.PRN", what=list(numeric(),numeric())); len =

Hi, I have been using R for a while. Recently, I have begun converting my package into S4 classes. I was previously using Rdoc for documentation. Now, I am looking to use the best tool for S4 documentation. It seems that the best choices for me are Roxygen and Sweave (I am fine with tex). Are there any users of Roxygen or Sweave who can comment on the strengths or weaknesses of one or othe

Hello list I'm a little confused about the R2 and adjusted R2 values reported by lm() when I try to fix an intercept. When using +0 or -1 in the formula I have found that the standard error generally increases (as I would expect) but the R2 also increases (which seems counter intuitive). I've pasted a short test script below to illustrate. I do realise that many will say I shouldn't be

Dear All, I am wondering on how to use the abline.xyplot with xyplot such that I will have different vertical lines for each panel. More sepcifically, suppose that the xyplot generates 4 panels defined by the combination of two binary variables: X_1 and X_2. i.e. xyplot(Y ~ Z | X_1*X_2, data = df) I want something like: abline(v = 5) if X_1=0 and X_2 = 0 abline(v =

L.S. I noticed the NEWS file as made available at http://cran.r-project.org/src/base/NEWS became inconsistent in describing CHANGES for a new R version: $ wget http://cran.r-project.org/src/base/NEWS $ cat NEWS | grep 'CHANGES IN ' CHANGES IN 3.2.0: CHANGES IN R 3.1.3: CHANGES IN R 3.1.2: CHANGES IN R 3.1.1: CHANGES IN R 3.1.0: CHANGES IN R 3.0.3: CHANGES IN R 3.0.2: CHANGES IN R 3.0.1:

The result of the code shown below is posted at the following URL: http://n2.nabble.com/Trying-to-properly-label-abline-td2524629.html I would like to figure out a better way to label the horizontal abline. I tried multiplying the text y position by a scale, but this didn't always put the text in a useful position. I guess I am curious if there is a preferred procedure for labeling the