similar to: Problem with the step() function

Dear All, I have data which contains 14 variables. And I have to regress one of variables on each variable (simple 13 linear regressions) I try to make a loop and store only R-squared colnames(boston) [1] "CRIM" "ZN" "INDUS" "CHAS" "NOX" "RM" "AGE" [8] "DIS" "RAD"

? data=read.table("http://statcourse.com/research/boston.csv", , sep=",", header = TRUE) ? library(rpart) ? fit=rpart (MV~ CRIM+ZN+INDUS+CHAS+NOX+RM+AGE+DIS+RAD+TAX+ PT+B+LSTAT) Please: Show me the tree. Mark -------- Original Message -------- Subject: Re: [R] help with rpart From: "Stephen Milborrow" <[1]milbo at sonic.net>

This question concerns rpart's facility for user-defined functions that accomplish splitting. I was interested in modifying the code so that in each terminal node, a linear regression is fit to the data. It seems that from the allowable inputs in the user-defined functions, that this may not be possible, since they have the form: function(y, wt, parms) (in the case of the

Dear all I am trying to fit Variable Coefficients Models on Unbalanced Panel Data. I managed to fit such models on balanced panel data (the example from the "plm" vignette), but I failed to do so on my real, unbalanced panel data. I can reproduce the error on a modified example from the vignette: > require(plm) > data("Hedonic") > Hed <- pvcm(mv ~ crim + zn + indus

Dear list members, I am trying to get information on how to fit a linear regression with constrained parameters. Specifically, I have 8 predictors , their coeffiecients should all be non-negative and add up to 1. I understand it is a quadratic programming problem but I have no experience in the subject. I searched the archives but the results were inconclusive. Could someone provide suggestions

Hi Friends, Same question has been asked on the Squid mailing list but so far no reply on the mailing list so posting it here also. We are trying to cache some files from apple.com like .dmg, .pkg, .ipa etc.. so that local clients can fetch the data from the cache. The problem we are facing is that we have download restrictions for every client to 25 MB during work hours except for a particular

FWIW, I wrote a little function to extract variable importance as defined in the CART book a while ago. It's rather limited: Only works for regression problem, and you need to set maxsurrogate=0 and maxcompete=0. It may (or may not) help you: varimp.rpart <- function(x) { dev <- x$frame[, c("var", "dev")] dev <- dev[dev$var != "<leaf>",

I have met into this problem when I tried to run panel regression by plm. My code: library(plm) indus <- read.csv(file="full.csv",header=TRUE) industry<-as.data.frame(indus) reg<-lm(LnTSO2 ~ LnPGDP + LnPGDP2 + LnSOES + LnCOES + LnLIMD + LnSHOLD + LnPRIV + LnFIEs + LnEXP + LnIMP + LnLEXRE + LnVALTAX + LnIND1 + LnIND2 + LnIND3 + LnIND4 + LnIND5 + LnIND6 + LnIND7 +

Hello, We would like more information on how to install the Samba suite. We are using SCO OpenServer Unix v 5.0 and want to interface with Windows NT 4.0 & Windows 98 clients. Note : We have downloaded the entire package from your site and tried to install it, but the first step (configuring Samba) couldn't be carried out as we could not locate the ".configure" file. The

? data=read.table("http://statcourse.com/research/boston.csv", , sep=",", header = TRUE) ? library(rpart) ? fit=rpart (MV~ CRIM+ZN+INDUS+CHAS+NOX+RM+AGE+DIS+RAD+TAX+ PT+B+LSTAT) predict(fit,data[4,]) plot only reveals part of the tree in contrast to the results on obtains with CART or C5 -------- Original Message -------- Subject: Re: [R] help with rpart From: Sarah

I have been running into difficulties with dispatching on an S4 class defined in the SparseM package, when the method calls are inside a function passed as the f= argument to optimize() in functions in the spdep package. The S4 methods are typically defined as: setMethod("det","matrix.csr", function(x, ...) det(chol(x))^2) that is within setMethod() rather than by name before

Dear R-users, Recently, I am facing some problems when converting mlbench data into matrix format. library(mlbench) data(BostonHousing) X<- BostonHousing[,1:13] y<-BostonHousing[,14] I want to convert X and y into matrix form. I am getting these obvious errors... > t(X)%*%y Error in t(X) %*% y : requires numeric/complex matrix/vector arguments > t(as.matrix(X))%*%(as.matrix(y))

I updated to the latest rc25 and started getting these messages(over and over again). This is on a Solaris 10 box and I tried compiling with gcc and sun c. I backed down to rc23 and the messages went away and everything works. Any body have an idea on what could be wrong? thank you dovecot: Mar 04 21:14:33 Error: child 467 (imap) killed with signal 6 dovecot: Mar 04 21:14:33 Error:

I am having problem using the step function for a linear regression model. I've created an initial model containing only the intercept. Then using the step function, I've selected three variables to be considered for the model. > x0.lm<- lm(MEDV~1, data = x) > > anova(x0.lm) Analysis of Variance Table Response: MEDV Df Sum Sq Mean Sq F value Pr(>F)

Dear R guru, I am Saikat Sarkar working as a researcher of Economics in Tampere University, Finland. I am trying to estimate some Garch related tests with Bayesian analysis by R programme. I am not good in R but trying to survive. Anyway I have the coding but not working properly. I have tried to find the problem but failed. I am writing to all R gurus to help me out. Could you please look at

> >  Dear moderators, Please help me encode the program instructed by follows. Thank u! Apply the methods introduced in Sections 4.2.1 and 4.2.2, say the > rank-based variable selection and BIC criterions, to the Boston housing > data. >  The Boston housing data contains 506 observations, and is publicly available in the R package mlbench (dataset “BostonHousing”).  The

Hi, I am trying to run an analysis of variance using R. in my data table "x" is a continuous variable lengthof 200 and "p" is a categorical variable also of length 200 and p is anyone of three categories 1,2 or ,3. if I run summary(aov(x~p,data=test)) I get Response: x Df Sum Sq Mean Sq F value Pr(>F) p 1 3174.7 3174.7 42.749 5.175e-10 ***

On Wed, 29 Nov 2000, Matt Pocernich wrote: > I am having problem using the step function for a linear regression model. I've created an initial model containing only the intercept. Then using the step function, I've selected three variables to be considered for the model. > > > > x0.lm<- lm(MEDV~1, data = x) > > > > anova(x0.lm) > Analysis of

On Wed, 29 Nov 2000, Matt Pocernich wrote: > I am having problem using the step function for a linear regression model. I've created an initial model containing only the intercept. Then using the step function, I've selected three variables to be considered for the model. > > > > x0.lm<- lm(MEDV~1, data = x) > > > > anova(x0.lm) > Analysis of

Hello, everyone I have a question. Assume I have the following zoo object: me.la <- structure(c(1524.75, 1554.5, 1532.25, 1587.5, 1575.25, 1535.5, 1550, 1493.5, 1492.5, 1472.25, 1457.5, 1442.75, 1399, 1535.75, 1565.25, 1543.5, 1598.5, 1586.5, 1547, 1561.5, 1504.75, 1503.75, 1483.75, 1468.75, 1453.75, 1410, 1546.75, 1575.25, 1554, 1609, 1597.5, 1558.5, 1573, 1516.25, 1515.5, 1495, 1480, 1465,