similar to: R-help Digest, Vol 36, Issue 21

Hello to all users and wizards. I am regulary using 'boxplot' function or its analogue - 'bwplot' from the 'lattice' library. But they are, as far as I understand, totally flawed in functionality: they miss ability to select what they would draw 'in the middle' - median, mean. What the box means - standard error, 90% or something else. What the whiskers mean -

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

I am running the ctree function in R. My data has about 10 variables, many of which are categorical. 2 of the categorical variables have many levels (one has 900 levels, another has 1,000 levels). As an example, 1 of these variables is disease code and is structured as A, B, C, ...., AA, AB, AC.... Each time i've tried to run the ctree function, including these 2

Hello, dear R-users. I have 2-d dotplot with two variables: x, y. Dots on this dotplot are grouped in human-recogniseable areas. These areas are not round-shaped nor oval-shaped. They are free-form, but still recogniseable by an operator. What is ability in R to graphically (per mouse) define some area and to select all the cases felt in it? 'identify' is OK for 5-10 cases, but what

Hello, dear R users. What is the easiest and the most visualli understandable way to analize dependency of numerical variable on two factors? Is the boxplot(y~f1+f2) the good way? It seems that this formula does not work. -- Evgeniy

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

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> ---

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

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

Like earth can be trained simultaneously for degree and nprune, is there a way to train ctree simultaneously for mincriterion and maxdepth? Also, I notice there are separate methods ctree and ctree2, and if both options are attempted to tune with one method, the summary averages the option it doesn't support. The full log is attached, and notice these lines below for

Dear all, I was intrigued by the ctree command and wanted to check it out. I first ran the demo with example(ctree) and did get the survival graphs in the end. Upon doing this with my own data and yielding a "Invalid operation on a survival time" I tried to rerun example(ctree) and now I also get "Invalid operation on a survival time" after the example runs plot(GBSG2ct)...

Hi Chris- Here''s a simpler version of the patch that drops the unrelated sync_fs stuff. thanks- sage The ''flushoncommit'' mount option forces any data dirtied by a write in a prior transaction to commit as part of the current commit. This makes the committed state a fully consistent view of the file system from the application''s perspective (i.e., it

I'm trying to understand how to set graphical parameters for trees created with the party package.  For example take the following code:   library(party)     data(airquality)     airq <- subset(airquality, !is.na(Ozone))     airct <- ctree(Ozone ~ ., data = airq,                    controls = ctree_control(maxsurrogate = 3))     plot(airct)   My problem is, I've got a ctree that has

When plotting Binary Trees (ctree) from the party package, is there a way to adjust the font sizes of the leaves? require(party) irisct <- ctree(Species ~ ., data = iris) plot(irisct) I want to adjust the font sizes for "Node 2", "Node 5", etc. I'd also like to be able to adjust the font sizes for the x-axis and y-axis labels of the histograms. Thanks,

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:

- Add incompat flag, otherwise btrfs-progs will report error when operating on btrfs filesystems mounted with lzo option. - Allow to turn on lzo compression for defrag operation: # btrfs filesystem defragment -c[zlib, lzo] <file> Note: "-c zlib" will fail, because that''s how getopt() works for optional arguments. Signed-off-by: Li Zefan

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

Hello, I've been using ctree and have developed a 55 node - 28 terminal solution. As can be imagined, the plot is difficult to travel down each of the major branches. I've read the help files for ctree I saw where terminal nodes can be color coded. plot(airct, type = "simple") > plot(airct, terminal_panel = node_boxplot(airct, col = "blue", + fill = hsv(2/3,

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")) {

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