similar to: interpreter change from RW1.7 to RW1.8 reviewed at RW1.9

Rein Klazes wrote: >On Wed, 23 Jun 2004 16:07:01 +0200 (CEST), you wrote: > > > >>I'm interested to have on the object of each message generated by the mailing list something like "[Wine]", as for others mailing lists. That could be useful to discriminate between right messages and spam, allowing to delete messages not reading them in advance. >> >>I

Hello List! I just set up a samba3+ldap pdc _almost_ successfully. If i log into the win2k box and i access \\123.123.123.123\user1 it asks me for my user1 passwd and i can access its home dir. But i can not log into the domain with the user1. It complains about a wrong passwd or user at the login prompt. Could it be that my machine is missing in my user databases? I did check my machine and it

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

Dear All, I have a question regarding predict.rpart. I use rpart to build classification and regression trees and I deal with data with relatively large number of input variables (predictors). For example, I build an rpart model like this rpartModel <- rpart(Y ~ X, method="class", minsplit =1, minbucket=nMinBucket,cp=nCp); and get predictors used in building the model like

Hi, I work with hyperspectral remote sensing data and I try to built a pls model with this data. I already built the model but if I try to calculate the RMSEP and R2 with a test data set I get the following error message: Error: variable 'subX' was fitted with type "nmatrix.501" but type "nmatrix.73" was supplied The problem is that I don't get the message for

I have a function that fits polynomial models for the orders in n: lmn <- function(d,n){ models=list() for(i in n){ models[[i]]=lm(y~poly(x,i),data=d) } return(models) } My data is: > d=data.frame(x=1:10,y=runif(10)) So first just do it for a cubic: > mmn = lmn(d,3) > predict(mmn[[3]]) 1 2 3 4 5 6 7 8

Moi! A student here has been getting a bit irritated with some side effects of scale() (OS is Windows XP, the behaviour occurs in R 2.0.0, but not 1.7.1). The problem is that she scales a variable in a data frame, then does a regression, and tries to get some predictions for some new data. However, at this point she gets an error (see the example below). This seems to be because the

One of the reports recently was of predict.lm misbehaving if newdata=data.frame(x=rep(NA, 10)) was given a logical column when it had been fitted as a numeric one. The exact problem was because model.matrix was trying to handle a 0-level factor (which is what that logical column got converted to by contrasts<-). However, the problem is more general and I have added to R-devel a layer of

  Hello All,   I am working with dlm for the purpose of estimating and forecasting with a Kalman filter model. I have succesfully set up the model and started generating results. Of course, I need to somehow be sure that the results make sense. Without any apparent target to compare with, my natural selection is the results by odinary least square. The idea being that if I choose a diffuse prior,

Hi all, I recently wrote some code to store a number of polynomial models in a list and return this list. The model is returned fine, but when I make a subsequent call to predict(), I have an error. The code for polyModel selection is listed at the end of the email. Here is an example of the error: > poly.fit <- polyModelSelection(x,y,10,F) > for (d in 1:4) { + lm.model <-

Hallo, I'll need a matrix with n rows of the an identical vector. > h [1] 3 3 3 3 2 2 2 The nmatrix should look like this: > x<-rbind(h,h,h) > x [,1] [,2] [,3] [,4] [,5] [,6] [,7] h 3 3 3 3 2 2 2 h 3 3 3 3 2 2 2 h 3 3 3 3 2 2 2 but I need n rows which must be variable. Can anyone help me? thanks Andreas

Hello, Is this a bug or a feature? I am using R 2.7.1 on Apple OS X. > y <- matrix(1:3,nrow=3) # y is a single-column matrix > df <-data.frame(x=1:3,y=y) > sapply(df,data.class) x y "numeric" "numeric" > df$yy <- y > sapply(df,data.class) x y yy "numeric" "numeric" "matrix"

Below is a SIMEX object that was generated with the "simex" function from the "simex" package applied to a logistic regression fit. From this mountain of information I would like to extract all of the values summarized in this line: .. ..$ variance.jackknife: num [1:5, 1:4] 1.684 1.144 0.85 0.624 0.519 ... Can someone suggest how to go about doing this? I can extract the

Hello! I'm puzzled by the following problem. It occurs while trying to predict responses in a test-dataset using a linear model fitted with regFit from the rMetrics "fRegression"-package. All goes well when I call "predict" using the training dataset. However, a call using the test-dataset retuns an error message - telling me that the latter dataset provides variables

Hello again, It appears that get_all_vars() incorrectly handles model formulae that use a right-hand side (rhs) matrix. For example, consider these two substantively identical models: # model using named variables mpg <- mtcars$mpg wt <- mtcars$wt hp <- mtcars$hp m1 <- lm(mpg ~ wt + hp) # model using matrix y <- mtcars$mpg x <- cbind(mtcars$wt, mtcars$hp) m2 <- lm(y ~ x)

Hi! We are pleased to announce the availibility of Gpg4win, version 1.0.3. * This version contains security fixes for the GnuPG and Sylpheed-Claws components. *Updating to this version is strongly recommended*. * Please also make sure to subscribe to the new gpg4win announcement mailing list. We might stop in the future to cross post announcements to the general GnuPG annoucement list.

Hi! We are pleased to announce the availibility of Gpg4win, version 1.0.4. * This version fixes a problem with several utilities like GPGee and parts of WinPT introduced with the last version. * Please make sure to subscribe to the new gpg4win announcement mailing list. We might stop in the future to cross post announcements to the general GnuPG annoucement list. See:

Hi! We are pleased to announce the availability of a new stable Gpg4win release: Version 1.1.4. This is a maintenance release; if you don't have any problems there is no need for an update. It mainly fixes problem using GnuPG on Windows Vista by updating to a newer version of the included GnuPG. About Gpg4win ------------- The Gpg4win project aims at updating the Gpg4win Windows

I am fittling a spline to a variable in a regression model, I am then using the predict.glm funtion to make some predictions. When I use bs to fit the spline I don't have any problems using the predict.glm function however when I use ns I get the following error: Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : variable lengths differ (found for

Hello, I hope this is the right mailing list for troubleshooting. My environment is: -CentOs 6.3 x64 -Samba as PDC -OpenLdap -Bind I followed this very nice tutorial to set-up the environment as PDC: http://www.server-world.info/en/note?os=CentOS_6 <http://www.server-world.info/en/note?os=CentOS_6&p=samba&f=4> &p=samba&f=4 And actually almost everything is