search for: regresssion

Dear R members, I have been trying to find out whether one can use multivariate regression trees (for example mvpart) to analyze repeated measures data. As a non-parametric technique, CART is insensitive to most of the assumptions of parametric regression, but repeated measures data raises the issue of the independence of several data points measured on the same subject, or from the same plot

Hello, I'm EDWIN, I create (make) GUI, with call many function but I don't know why when I call function I can't. if without function, Yes I can.. can you help me ? can you make this, become true with full code? Can you help me to create data.entry with interface LM - BETA1.HAT - BETA2.HAT SD.BETA1.HAT HAT SD.BETA2.HAT RLM - BETA1.HAT - BETA2.HAT SD.BETA1.HAT HAT SD.BETA2.HAT 2 10

Is there a way to get confidence intervals around an ordered regression like polr() in the MASS package? ------------------------------------------- Joe King, M.A. Ph.D. Student University of Washington - Seattle 206-913-2912 <mailto:jp@joepking.com> jp@joepking.com ------------------------------------------- Ad astra per aspera - "Through hardships to the stars"

I am trying to find out if someone has implemented a (McFadden-type) multivariate binary logistic regresssion package for R? From what I can tell, this is not available for R. Thank you, Lynne Baker [[alternative HTML version deleted]]

I've been using R to do logistic regresssion, and that's working well, but there are two things I haven't figured out how to do. (1) Is there some pre-existing function that will let you compute the odds ratios and confidence intervals for them for a specific fit. I know how to do this manually or even write a function that I...

A couple of questions: How to be sure that gls allowes errors to be correlated and/or have unequal variances? (is this on auto or is there a switch?) How to calculate confidence limits for a linear regresssion? -------------- next part -------------- A non-text attachment was scrubbed... Name: dthompson.vcf Type: text/x-vcard Size: 303 bytes Desc: Card for David Thompson Url : https://stat.ethz.ch/pipermail/r-help/attachments/20011227/680f2687/dthompson.vcf

...0.81 1.26 2.30 plot(x,y) I want to be able to force the line of the model(mymodel<-lm(y~z)) to pass through the origin (zero) and the line of the model(mymodel<-lm(y~x)) to pass through 10 as an x-intercept. For the first case i have used the (y~x-1) syntax, but the linear model returned a regresssion that didn't pass trough the points (with a higher Rsq than expected). For the second case, i did not find a solution yet.. Could somone help me please? Thanks in avance Walid SADOK

Dear all: Does anyone has harmonic regresssion analysis package written in R (to be used in Windows platform) ? Thanks _______________________________________ YM - Â÷½u°T®§ ´Nºâ§A¨S¦³¤Wºô¡A§AªºªB¤Í¤´¥i¥H¯d¤U°T®§µ¹§A¡A·í§A¤Wºô®É´N¯à¥ß§Y¬Ý¨ì¡A¥ô¦ó»¡¸Ü³£ÉN¨«¥¢¡C http://messenger.yahoo.com.hk [[alternative HTML version deleted]]

Hi All, I am working on some ordinal logistic regresssions using LRM in the Design package. My response variable has three categories (1,2,3) and after using the creating my model and using a call to predict some values and I wanted to use a simple .5 cut-off to classify my probabilities into the categories. I had two questions: a) first, I am hav...

...; and 1,855 cases. Trying the following: > > The DV is categorical, 0 or 1. Most of the IV's are either > continuous, or > correctly read in as factors. The largest factor has 30 > levels.... Only the > DV seems to need identifying as a factor to force class trees over > regresssion: > > >Mydata$V46<-as.factor(Mydata$V46) > >Myforest.rf<-randomForest(V46~.,data=Mydata,ntrees=100,mtry=7 ,proximities=FALSE > , importance=FALSE) > > 5 hours later, R.bin was still taking up 75% of my processor. > When I've > tried this with larger data,...

...that to show that SPSS has way to generate that.though "Residuals" row is generated in R just like SPSS. I know the how to calculate a single summarized Df,Sum Sq,Mean Sq,F value,Pr(>F) with these formulae:--- *That is instead of all the 15 rows from reacmeanC1 to i15 i want row "Regresssion"* Df Sum Sq Mean Sq F value Regression Calculations sum of all the above dfs sum of all the above Sum of Squares Sum of Squares/df Mean Square due to Regression/Mean Square due to Residuals But isn't there any function...

...t the code, randomForest used an exhaustive search over all possible splits. Try reducing the number of levels to something reasonable (or for a first shot: remove this variable from the learning sample). Best, Torsten > DV seems to need identifying as a factor to force class trees over > regresssion: > > >Mydata$V46<-as.factor(Mydata$V46) > >Myforest.rf<-randomForest(V46~.,data=Mydata,ntrees=100,mtry=7,proximi > >ties=FALSE > , importance=FALSE) > > 5 hours later, R.bin was still taking up 75% of my processor. When > I've tried this with larger data...

Folks, Two simple questions : (1) I have a data set (call it data.xls) in a folder in my hard drive. How do I perform a simple regression between two variables from that data set? After I click on 'R', what exactly do I type in? (2) Where do I get to see the complete library of packages offered by R? In particular, I am interested in quantile regression and logistic regression.

Dear R-help, I have a four-part question about regression, matrices, and sandwich package. 1) In the sandwich package, I would like to better understand the meat() function. >From the bread() documentation, for a simple OLS regression, bread() returns (1/n * X'X)^(-1) That is, for a simple regression (per the documentation on bread()): MyLM <- lm(y ~ x) bread(MyLM)

At 12:01 03/04/04 +0200, you wrote: >Content-Transfer-Encoding: 8bit >From: solares at unsl.edu.ar >Precedence: list >MIME-Version: 1.0 >Cc: >To: R-help at stat.math.ethz.ch >Date: Fri, 2 Apr 2004 12:47:48 -0300 (ART) >Message-ID: <50155.209.13.250.66.1080920868.squirrel at inter17.unsl.edu.ar> >Content-Type: text/plain;charset=iso-8859-1 >Subject: [R] convert

I would like to use R to perform a logistic regression with about 30,000 independent variables. That's right, thirty thousand. Most will be irrelevant: the intent is to use the regression to identify the few that actually matter. Among other things, this calls for giving glm() a colossal "y ~ ..." formula with thirty thousand summed terms on its right hand side. I build up the

...were used: - In guest side, try to use delayed callbacks as much as possible. - In host side, try to use interrupt coalescing for reduce interrupts. About 10% - 15% performance were improved with this. Perforamnce test shows: - Few regression (10% - 15%) were noticed TCP_RR were noticed, this regresssion were not seen in previous version. Still not clear the reason. - CPU utilization is increased in some cases. - All other cases, tx interrupts can perform equal or better than orphaning especially for small packet tx TODO: - Try to fix the regressions of TCP_RR - Determine a suitable coalescing...

...were used: - In guest side, try to use delayed callbacks as much as possible. - In host side, try to use interrupt coalescing for reduce interrupts. About 10% - 15% performance were improved with this. Perforamnce test shows: - Few regression (10% - 15%) were noticed TCP_RR were noticed, this regresssion were not seen in previous version. Still not clear the reason. - CPU utilization is increased in some cases. - All other cases, tx interrupts can perform equal or better than orphaning especially for small packet tx TODO: - Try to fix the regressions of TCP_RR - Determine a suitable coalescing...