similar to: linear regression, log-transformation and plotting

Hello, I have a basic question. Sorry if it is so evident.... I have the following data file : http://ekumen.homelinux.net/mydata.txt I need to model Y~X-1 (simple linear regression through the origin) with these data : load(file="mydata.txt") X=k[,1] Y=k[,2] aa=lm(Y~X-1) dev.new() plot(X,Y,log="xy") abline(aa,untf=T) abline(b=0.0235, a=0,col="red",untf=T)

Dear all,?I am trying to fit a multiple linear regression model with a transformed dependant variable (the normality assumption was not verified...).?I have realised a sqrt(variable) transformation...?The results are great, but I don't know how to interprete the beta coefficients... Is it possible to do another transformation to get interpretable beta coefficients to express the variations in

Hello, R-Help answers questions on R code, your question is about statistics. You should try posting the question to https://stats.stackexchange.com/ Hope this helps, Rui Barradas Em 23-10-2017 18:54, kende jan via R-help escreveu: > Dear all, I am trying to fit a multiple linear regression model with a transformed dependant variable (the normality assumption was not verified...). I have

Dear list (but probably mostly Hadley): In ggplot, operations to modify 'guides' are accessed through grid objects, but I did not find mention of creating new guides or possibly removing them altogether using ggplot functions. I wonder if this is something I need to learn grid to learn more about (which I hope to do eventually). Also, ggplot()+geom_object() [where 'object' can be

I am trying to plot the results of a random effects model where each subject is allowed to have his, or her, own intercept. I use xyplot to plot the data, lme to compute the regression and then try to put a summary regression line on the xyplot. As can be seen by the output pasted below, I am getting an error message, Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : (list)

Hi folks, Win7 64bit R 1.12.0 I run following command on R:- > ToothGrowth > attach(ToothGrowth) > plot(dose,len) > matrics=lm(len~dose) > abline(metrics) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet Only a grey diagram is displayed without content > plot(abline(metrics)) Error in int_abline(a = a, b = b, h = h, v

I have a data vector x. When I try qqline(x) I get the following error: Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet And a blank plot appears. Can anybody help? What am I doing wrong? Thanks, Scotty _________________________________________________________________ Contest [[alternative HTML version deleted]]

Dear whom it may concerns, I am Jia Xu, a summer intern analyst at Citi Research. I am also a graduate student studying Financial Engineering at Cornell. I am running regression analysis with Rstudio now. I have been experiencing difficulty with the abline function. No matter I call it directly in linear regression or call it through residual plots, or plot results from lasso regression, it

Full_Name: Stephen Eglen Version: 1.4 OS: Redhat Linux 7.1 Submission from: (NULL) (128.252.204.36) abline() produces a spurious line in addition to the correct line, at least with the X11 driver. The postscript file generated also has nan values in it, which causes an error under ghostscript. xs <- c(0, 150, 300) ys <- c(75, 40, 23) par(mfrow=c(1,2)) plot(xs,ys, log="")

Dear R-users, I am using R(a package igraph) to calculate certain topological features of networks. When I try to draw a plot between these features I get an error. Following is the code I am using : *> plot(met_eco_deg,met_eco_bet) > lmout<-lm(met_eco_bet ~ met_eco_deg) > abline(lmout) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new

I really want to do this: abline( a=tan(-kT*pi/180), b=kY-tan(-kT*pi/180)*kX ) where kX,kY and kT are vectors of equal length. But I can't do that with abline unless I use a loop, and I haven't figured out the least unelegant way of writing the loop yet. So is there a way to do this without a loop? Or if I am to resort to the loop, what's the best way of doing it considering that I

Hi, I want to have a horizontal line on a mosaic plot with "vcd" package. This would give me an idea where is 0.5 proportion in a cell. Using "mosaicplot" function of "graphics" package, I can draw a line using "abline." But, with "mosaic" function of "vcd" package, I have tried to use "abline" function, which complains

I have a Mac OS X system. To deal with a long monthly electricity demand time-series I use the procedures TRAMO/SEATS with the MS-windows only Demetra programme and X12 under R resorting to the awkward - as far as the output is concerned - x12 R package running the relating Fortran code. I wonder if someone out there has attempted to translate TRAMO/SEATS and X12 into R native language? Ciao

Hello, I ran AIC for some competing models I created. I get df and an AIC score from the AIC procedure. Can I use the models with the lowest AIC scores from this procedure to choose my 'best' models? If not, what else do I need to do (and know) and how can I do it in R to chose the 'best' models? Thank you kindly, Michael [[alternative HTML version deleted]]

I'm working over an ssh connection without X11 graphics. I'm making a plot, the first stage of drawing which takes a long time. I want to experiment with adding details. Here is what I was hoping to do, which results in error. ## Draw the master plot on png dev 2 png(file="master.png") plot(1:10) ## Save a copy on png dev 3 png(file="copy1.png") dev.set(2)

I would like to add two horizontal lines representing acceptible drug levels to a trellis plot. I tried using abline and I get an error that "plot.new has not been called." See below. xyplot(FK~WEEK|Event1/MRN, data=FKdat.o1) abline(h=5) abline(h=10) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet Any help that can be provided

Hello!!, for linear models fit I use Gretl, but now I'm starting to use R, I would like to know if is there some function to obtain a extended summary like in Gretl. I will write a example in Gretl Modelo 1: MCO, usando las observaciones 1968-1982 (T = 15) Variable dependiente: Invest Coeficient St error t-ratio p-value const 377,631 35,0955 10,7601 <0,00001 *** GNP

Hallo, as I see there is a new version for R available. Can anyone tell me how I can update my version 2.5.0 under Windows? The last times I just uninstalled the old version and installed the new one. Afterwards I had to install also all needed packages again. All in all it cost me half a day until my system works fine again. Is there a quicker option? If yes please tell me the commands. Thanks,

Hello all, I looking at package dse or vars or mAr I know how to simulate a VAR(p) process, my problem is that most of those processes are unstable (not weakly stationary). Do anybody know how to generate a random VAR (or VARMA even better) process that is weakly stationary? Thanks -- View this message in context: http://r.789695.n4.nabble.com/simulating-stable-VAR-process-tp4261177p4261177.html

When I do ARMA(2,2) using one lag of LCPIH data This is eview result > > *Dependent Variable: DLCPIH > **Method: Least Squares > **Date: 08/12/11 Time: 12:44 > **Sample (adjusted): 1970Q2 2010Q2 > **Included observations: 161 after adjustments > **Convergence achieved after 14 iterations > **MA Backcast: 1969Q4 1970Q1 > ** > **Variable Coefficient Std.