similar to: problem

Hi Anne, I would suggest to change the linear model to lm(BloodPressure~Age), as this model makes more sense in biological means (you would assume that age influences pressure, not vice versa) and also obeys the statistical assumption of weak exogeneity, that age can be measured without error, at least compared to error-prone bp measures. Cheers Am 18.04.2018 um 16:07 schrieb Gerrit Eichner:

Hi all, I'm fitting a linear model (using lm) to some 2500 data points. The model consists of 4 single terms and two combined terms. I get the following warning message: "Extra arguments projections are just disregarded. in: lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) " Can anybody clarify this ? I don't seem to find any pointer to what this might

Hello, I would like to display two groups of dots in different colors or style and additionnaly a linear regression for all the dots in panel plots of a Trellis graph. Actually to get in each panel the equivalent of: plot(x[mois==3],y[mois==3],col="blue") points(x[mois==9],y[mois==9],col="red") abline(lm(y~x), col="green") "mois" being a grouping

Hello! I'm still working on my problem, which also occurs with the predict.lm() function. - Providing newdata, which is a data.frame with all variables being "numeric", as str() shows, R tells me the following: ar1.xpred.test.pred <- predict(ar1.xpred.fitted, regdata.test, se.fit = FALSE) Fehler: variable 'lag(ret1)' was fitted with type "numeric" but type

Hello R-user I want to compute a multiple regression but I would to include a check for collinearity of the variables. Therefore I would like to use a ridge regression. I tried lm.ridge() but I don't know yet how to get p-values (single Pr() and p of the whole model) out of this model. Can anybody tell me how to get a similar output like the summary(lm(...)) output? Or if there is

I have troubles installing the "SparseM" package on my Debian stable Linux system. Debian's version of R is: platform i386-pc-linux-gnu arch i386 os linux-gnu system i386, linux-gnu status major 1 minor 5.1 year 2002 month 06 day 17 language R This is the installation output: > R CMD INSTALL -l /usr/lib/R/ SparseM_0.36.tar.gz * Installing

Hi Martin, When I attended the LinuxWorld Expo in NYC back in January, I chatted with some folks at the AMD booth, as well as guys from Penguin Computing (where we bought our Opteron box). I was told that the Operton has this somewhat strange setup that the memory is controlled by one CPU. The net effect of this being that when both CPUs are running, one might only be running at around 90%

Hello dear R users, My objective is to change the size of this graphic : plot(lm(a~b), 4) (Cook's distance) I have found the help on the internet saying to change the size of a title on a graphic plot(lm(a ~ b), 4), I should use the graphic parameter cex.caption http://stat.ethz.ch/R-manual/R-patched/library/stats/html/plot.lm.html But in my install of R, it answers cex.caption isn't a

Hi all, Say I fit a linear model, and saved it as 'test.lm' Then if I use plot(test.lm) it gives me 4 graphs How do I ask for a 'subset' of it?? say just want the 1st graph, the residual vs fitted values, or the 1,3,4th graph? I think I can use plot(test.lm[c(1,3,4)]) before, but now, it's not working... Every time, it goes to the end, the only thing I can click is

Subject: Re: [R-sig-Debian] ubuntu problem with 'r-cran-robustbase' [FWD Agustin Lobo] Date: Tue, 12 May 2009 13:30:49 +0200 From: Agustin Lobo <aloboaleu at gmail.com> Reply-To: aloboaleu at gmail.com To: Dirk Eddelbuettel <edd at debian.org> CC: Martin Maechler <maechler at stat.math.ethz.ch>, R-SIG-Debian at stat.math.ethz.ch References: <18953.17704.527898.355877

Hi, I am a new user of R 2.8.1. I use Tinn-R for code editing. I use a windows 2003 system with 1 GB RAM. I am interested to generate dashboard and reports based on data from MS Access. These reports need to be posted on a weekly basis to the web. The reporting interface should provide facilities for "what if" scenarios. Is it possible to interface R analysis results to good open

Hi, I am out of town and will get back to you on the 13th of July. Leo >>> "r-help at stat.math.ethz.ch" 06/27/03 00:32 >>> Send R-help mailing list submissions to r-help at stat.math.ethz.ch To subscribe or unsubscribe via the World Wide Web, visit https://www.stat.math.ethz.ch/mailman/listinfo/r-help or, via email, send a message with subject or body

Hi! Some weeks ago I discovered R. Now, I have a somewhat complicated task and am not sure whether R is the right tool to solve it. I got data of several series or measurements where I have to find the two inflection points. I did a linear regression (with ^2 and ^3 arguments), the problem there was that I had to look only at a very narrow band of measurement in order to get the

Dear Martin, I think that your plan makes sense. It's too bad that aov() behaved differently in this respect from lm(), and thus created more work, but it's not be a bad thing that the difference is now explicit and documented. I expect that that other problems like this will surface, particularly with contributed packages (and I know that you're aware that this has already happened

HI, This code is part of a code I used to do a linear regression: >points(var1~var2,data=Regress,pch=21,bg="grey") >reg11<-lm(var1~var2,data=Regress) >abline(lm(var1~var2,data=Regress),lty=2,lwd=2,col="grey") >legend("topleft",legend= >c("NDII from composite", >"y= 0.0007x - 0.1156",expression(paste(r^2 ==

Hi, Anne, assign Age and Bloodpressure in the correct order to the axes in your call to plot as in: plot(y = Age, x = BloodPressure) abline(SimpleLinearReg1) Hth -- Gerrit --------------------------------------------------------------------- Dr. Gerrit Eichner Mathematical Institute, Room 212 gerrit.eichner at math.uni-giessen.de Justus-Liebig-University Giessen Tel:

Dear Martin, I made three points which likely got lost because of the way I presented them: (1) Singularity is an unusual situation and should be made more prominent. It typically reflects a problem with the data or the specification of the model. That's not to say that it *never* makes sense to allow singular fits (as in the situations you mentions). I'd favour setting

Hi folks, I created a subset of a dataframe (i.e., selected only men): subdata <- subset(data,data$gender==1) After a residual diagnostic of a regression analysis, I detected three outliers: linmod <- lm(y ~ x, data=subdata) plot(linmod) Say, the cases 11,22, and 33 were outliers. Here comes the problem: When I want to exclude these three cases in a further regression analysis, - for

>>>>> Fox, John <jfox at mcmaster.ca> >>>>> on Thu, 14 Sep 2017 13:46:44 +0000 writes: > Dear Martin, I made three points which likely got lost > because of the way I presented them: > (1) Singularity is an unusual situation and should be made > more prominent. It typically reflects a problem with the > data or the

Hi Everyone, I just don't know how to extract the information I want from the summary of a linear regression model fitting. For example, I fit the following simple linear regression model: results = lm(y_var ~ x_var) summary(results) gives me: Call: lm(formula = y_var ~ x_var) Residuals: Min 1Q Median 3Q Max -5.9859 -1.5849 0.4574 2.0163 4.6015 Coefficients: