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...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 + chas + nox + rm + age + dis +rad + tax + ptratio + blacks + lstat, Hedonic, model = "within",index = "townid") Error in FUN(X[[1L]], ...) : insufficient number of observations > ##it fails for both FE and RE cases > Hed <- pvcm(mv ~ crim + zn + indus + chas + nox + rm...

...s are appreciated. I've prepared a simple example to illustrate my problem: > library(MASS) > data(Boston) > my.fun <- function(dataset) { + l <- lm(medv ~ .,data=dataset) + final.l <- step(l) + } > model <- my.fun(Boston) Start: AIC= 1589.64 medv ~ crim + zn + indus + chas + nox + rm + age + dis + rad + tax + ptratio + black + lstat Df Sum of Sq RSS AIC - age 1 0.1 11078.8 1587.6 - indus 1 2.5 11081.3 1587.8 <none> 11078.8 1589.6 - chas 1 219.0 11297.8 1597.5 - tax 1 242.3...

...y_max_size 500000000 allow WorkingHours2 google reply_body_max_size 500000000 allow WorkingHours3 google reply_body_max_size 5000000 allow WorkingHours2 youtube reply_body_max_size 5000000 allow WorkingHours1 youtube reply_body_max_size 50000000 allow WorkingHours3 youtube http_access allow google indus http_access allow youtube indus reply_body_max_size 26000000 allow WorkingHours1 all reply_body_max_size 26000000 allow WorkingHours2 all reply_body_max_size 50000000 allow WorkingHours3 all http_access allow allowindus WorkingHours4 http_access allow indus Do let me know if you need any further...

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 + Ln...

? 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> Date: Fri, July 29, 2011 7:54 am To: <[2]mark at statcourse.com&gt...

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" "TAX" "PTRATIO" "B" "LSTAT" "MEDV" name <- colnames(boston) r <- rep(0, 13) for(i in 1: 13) { r[i...

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

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

? 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 Goslee <sarah.goslee at gmail.com> Date: Fri, July...

...re the setMethod(). When called from within functions passed as the f= argument to optimize, the S3 generics for det() and chol() get picked up, not the S4 generics for the S4 SparseM classes. This looks for instance like (from example(boston)): > gp2 <- lagsarlm(log(CMEDV) ~ CRIM + ZN + INDUS + CHAS + I(NOX^2) + I(RM^2) + + AGE + log(DIS) + log(RAD) + TAX + PTRATIO + B + log(LSTAT), + data=boston.c, nb2listw(boston.soi), method="SparseM") matrix.csr Error in chol(tmp1) : non-numeric argument to chol (this is the error message in chol.R in base). tmp1 is of class "mat...

...is.na(imp)] <- 0 imp } Here's an example using the Boston housing data: > library(rpart) > data(Boston, package="MASS") > boston.rp <- rpart(medv ~ ., Boston, control=rpart.control(maxsurrogate=0, maxcompete=0)) > varimp.rpart(boston.rp) crim zn indus chas nox rm age dis 1136.809 0.000 0.000 0.000 0.000 23825.922 0.000 1544.804 rad tax ptratio black lstat 0.000 0.000 0.000 0.000 7988.955 Both gbm and randomForest has analogous measures. Andy > From: We...

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))

...gt; 0x3f118 -> 0x6b1f8 -> 0x29634 -> 0x2105c -> 0x211f0 -> 0x22c3c -> 0x22bb4 -> 0x22db0 -> 0x7f7d8 -> 0x7f090 -> 0x2b188 -> 0x1db88 dovecot: Mar 04 21:14:34 Error: child 473 (imap) killed with signal 6 -- Brett Morrow, NSSL Senior Systems and Storage Adminstrator INDUS Corporation National Severe Storms Laboratory (405) 366-0515 Brett.Morrow at noaa.gov http://www.induscorp.com -------------- next part -------------- A non-text attachment was scrubbed... Name: brett.morrow.vcf Type: text/x-vcard Size: 363 bytes Desc: not available URL: <http://dovecot.org/pip...

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

I'll release v1.0.1 in a day or two, but it would be nice to get some testing before the release to see if I managed to break something after the Mercurial conversion. And did I forget something that should be fixed for v1.0.1? http://dovecot.org/tmp/dovecot-1.0.1rc2.tar.gz Changes since v1.0.0: * deliver: If Return-Path doesn't contain user and domain, don't try to bounce the

I want to take the first row of each unique ID value from a data frame. For instance > ddTable <- data.frame(Id=c(1,1,2,2),name=c("Paul","Joe","Bob","Larry")) I want a dataset that is Id Name 1 Paul 2 Bob > unique(ddTable) Will give me all 4 rows, and > unique(ddTable$Id) Will give me c(1,2), but not accompanied by the name column.

Hi all, Has anyone used the qua.regressCOP2 function from the copBasic package??? The default copula function used in this function is plackett copula and I wanted to use archimedean copula. Attached below is my code: mycop<-frankCopula V=seq(0.001,0.99,by=0.000217) R<-qua.regressCOP2(0.25,V,cop=mycop,para=c(3.504)) And this is the error I get: Warning messages: 1: In