similar to: ctree and survival problem

Hi All, I'm using the party package to grow conditional inference trees for survival analysis. When I used party version party_0.9-9991 everything worked well, but when I update to party_1.0-2 (due to using 64bit R), I get an error. For simplicity I will show the error I get for the example in the party documentation: ### survival analysis if (require("ipred")) {

Hola a todos, estoy procesando unos datos con las siguientes intrucciones que creo son del paquete stats: cloud(Imp89 ~ ImpTot89 * NDA | Edad, data = mtif, +       screen = list(x = -90, y = 45), distance = .4, zoom = .7) y obtengo el error: Error en eval(substitute(groups), data, environment(formula)) :  argumento ''envir'' númerico no tiene longitud uno La verdad es que no se

Dear R?ers I?m trying to get a summary table using latex and summary in the rms package to no avail. I?m running R 2.10.1, Mac OS X snow leopard and I have the mactex 2009 distribution installed. Any obvious things I?m missing? //M options(digits=3) set.seed(173) sex <- factor(sample(c("m","f"), 500, rep=TRUE)) age <- rnorm(500, 50, 5) treatment <-

Some help with how to re-label the vertical axis in a histogram would be appreciated. qplot(off.sc,weight=rel.freq,binwidth=.29,main="test Figure"+ylab("New from inside"))+ylab("New from outside")+ xlab("off.sc\nAggregated frequency plots for 17 equal intervals.") The code

Dear all, I just received a file from a colleague in spss. The read.spss could not finish the file due to an error (Unrecognized record type 7, subtype 18 encountered in system file) so instead I converted the file using stat-transfer. Looking at my data I see that most labels are in the attributes and I?d love to access them and assign the pertinent variables to factors without doing the whole

The commit 607d432d referred a static int array defined in ctree.h, and a static inline function (btrfs_super_csum_size) using this array, the obvious problem is every c file using that function would have a local copy of that int array, multiple c files calling would result multiple copies of that array: $ nm fs/btrfs/btrfs.ko | grep btrfs_csum_sizes 0000010c r btrfs_csum_sizes 00000114 r

Dear R´ers.. In this mock dataset how can I generate a logical variable based on whether just tes or tes3 are NA in each row?? test<-sample(c("A",NA,"B"),100,replace=T) test2<-sample(c("A",NA,"B"),100,replace=T) test3<-sample(c("A",NA,"B"),100,replace=T) tes<-cbind(test,test2,test3)

Dear all, Given rr<-data.frame(r1<-rnorm(1000,10,5),r2<-rnorm(1000,220,5)) How can I add a column (rr$p) for the joint probability of each r1 & r2 pair? I know how to add the column.. I just dont know how to compute the p value for joint probabilities given the two samples. //M

Hello, This is a re-submittal of question I submitted last week, but haven't rec'd any responses. I need to extract the probabilities used to construct the barplots displayed as part of the graph produced by plot("ctree"). For example, library(party) iris.ct <- ctree(Species ~ . , data = iris) plot(iris.ct) Instead of a simple example with only 4 terminal nodes, my

Hi, I have a problem with ctree of party package. I have data on distribution of more than one species (about 50 species) and I would like identify the relation of this multivariate object (species distribution) with a number of explanatory variables. rs is the name of my dataframe containing the species (columns from 2 to 51) and the explanatory variables (columns 52 and 53). Rows are my

Hello, I noticed a double definition of BTRFS_CSUM_TYPE_CRC32 in ctree.h and attach a patch that removes it. Best regards, Dirk

Dear R?ers. I?ve got a dataset with age and year of diagnosis. In order to age-standardize the incidence I need to transform the data into a matrix with age-groups (divided in 5 or 10 years) along one axis and year divided into 5 years along the other axis. Each cell should contain the number of cases for that age group and for that period. I.e. My data format now is ID-age (to one

I tried to use ctree but am not sure about the meaning of the plot. My.data.ct<-ctree(Resp~., data=My.data) plot(My.data.ct) My data.frame contains 88 explanatory variables (continous,ordered/unordered multistate,count data) and one response with two groups. In the plot are only two variables shown (2 internal nodes) and 3 final nodes. Does it mean that only these two variables show a

Hello, I need to classify (i.e., export a vector with terminal node id's) new cases using a ctree (party package) model based on different cases (learning sample). I tried the where command with the following syntax: > where(tree, newdata=data2) expecting to get terminal nodes of data2 cases based on rules of tree model (data1 as learning sample). However it returned the following error

When the binary search returns 0 (exact match), the target key will necessarily be at slot 0 of all nodes below the current one, so in this case the binary search is not needed because it will always return 0, and we waste time doing it, holding node locks for longer than necessary, etc. Below follow histograms with the times spent on the current approach of doing a binary search when the

If we have particularly full nodes, we could call btrfs_node_blockptr up to 32 times, which is 32 pairs of kmap/kunmap, which _sucks_. So go ahead and map the extent buffer while we look for readahead targets. Thanks, Signed-off-by: Josef Bacik <josef@redhat.com> --- fs/btrfs/ctree.c | 23 +++++++++++++++++++++-- 1 files changed, 21 insertions(+), 2 deletions(-) diff --git

Hello Josef, FYI build failure occured in fs/btrfs/ctree.h. CC fs/btrfs/super.o In file included from fs/btrfs/delayed-inode.h:30:0, from fs/btrfs/super.c:45: fs/btrfs/ctree.h:3235:1: error: expected identifier or ‘(’ before ‘<<’ token make[3]: *** [fs/btrfs/super.o] Error 1 make[2]: *** [fs/btrfs] Error 2 make[1]: *** [fs] Error 2 make[1]: Leaving directory ` make:

Hello, I want to import R-output via Rserve to Java, especially for the function ctree from the package party. Rserve is working properly. Yet, I only get the predictions with the Java code try{ RConnection c = new RConnection(); ... c.voidEval("modell <- ctree(...)"); REXP y = c.eval("nodes(modell,1)[[1]]$prediction"); ...

When replaying a log tree with qgroups enabled, tree_mod_log_rewind does a sanity-check of the number of items against the maximum possible number. It calculates that number with the nodesize of fs_root. Unfortunately fs_root is not yet set at this stage. So instead use the nodesize from tree_root, which is already initialized. Signed-off-by: Arne Jansen <sensille@gmx.net> ---

glm(A~B+C+D+E+F,family = binomial(link = "logit"),data=tre,na.action=na.omit) Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : contrasts can be applied only to factors with 2 or more levels however, glm(A~B+C+D+E,family = binomial(link = "logit"),data=tre,na.action=na.omit) runs fine glm(A~B+C+D+F,family = binomial(link =