similar to: How to recursively build a binary tree with R script?

I could use some help generating a time series for the Mackey-Glass equation: dx/dt = 0.2 x(t-tau)/(1 + x(t-tau)^10) - 0.1 x(t) for the case there tau = 17. I tried the "ddesolve" package but the dde(...) function seems to hang, not producing anything. Can someone show me the R script how to do this? - Mike Beddo [[alternative HTML version deleted]]

Greetings, When I try "install.packages('Rcpp')" it fails when compiling api.cpp (line 39). This is Rcpp 0.11.3. I searched my filesystem, and indeed I do not have execinfo.h anywhere. After some effort, I got R build on AIX. Now I am trying to build the packages I need. Rcpp is crucial. I first build R with the native IBM XL compilers, and Rcpp wouldn't build. That was

Hi I am new with R I Have to build a binary tree with R. I'm very confused was wondering if anyone had any R sample code they would share. I've come across a lot of C++ code(nothing in R) and this is not helping. Any bady can help me? Bye Giuseppe -- View this message in context: http://r.789695.n4.nabble.com/building-binary-tree-tp4634592.html Sent from the R help mailing list

I'm using R version 1.5.1, and Microsoft Developer Studio 97 (yes, I know it's old, but it's expensive to upgrade) on Windows 98. I created the DLL file with the compiler. The name of the file containing the subroutine is leaf.f and the subroutine is named leaf.f. In my R program (which defines a function called leaf), I have x <- .Fortran("leaf",...) where the ...

Hi, I have a licensing question: I'm curious if the fact maketree.py is GPLv2 causes any trouble for the rest of rsync (which is GPLv3 or later). -- yours, Julius Davies 250-592-2284 (Home) 250-893-4579 (Mobile) http://juliusdavies.ca/logging.html

> fit.dimer <- rpart(as.factor(out) ~ ., method="class", data=p_df) > > fit.dimer$frame[, "var"] [1] NE WC <leaf> TA <leaf> <leaf> WG WD WW WC [11] <leaf> <leaf> <leaf> CT <leaf> FC <leaf> YG QT <leaf> [21] <leaf> <leaf> NW DP DY <leaf> SK

I'm a newcomer to R. I can't seem to find any documentation how to add error bars to points in scatter plots. I guess I could plot the points, then compute and plot line segments in the X and/or Y directions to represent the errors? - Mike -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear mailinglist members, I was wondering if there was a way to re-evaluate the instances of a tree (in the forest) again after I have manually changed a splitpoint (or split variable) of a decision node. Here's an illustration: library("randomForest") forest.rf <- randomForest(formula = Species ~ ., data = iris, do.trace = TRUE, ntree = 3, mtry = 2, norm.votes = FALSE) # I am

Hi Mark/Joel, These are 2 bug fix for b-tree. Please review. I have sent out the first one last week, but it was based on cacheme. So resend it. Now it bases on joel's fixes branch. The second one is another b-tree rotation bug. I guess the reason why we never meet with it is that no one has ever used b-tree like reflink before. ;) Regards, Tao

friends, I need some tool to visualize the results of hierarchical clustering. Specifically, I want to plot it as a radial plot as a phylogenetic tree. In addition, I want to specify the color to each leaf node. I search all phylogenetic tree plotting routines here, they all cannot show the leaf nodes and their colors. Since i will have a lot of leaf nodes, the color needs to be specified and

Dear Prof Azzalini, You have an interesting example of recursive use of uniroot(). [re-cited at the end] However, note that R currently has the same problem as S-plus: Uniroot() doesn't work reliably, recursively. When you found it to be better, you were just lucky. The relevant file in R's source, src/main/optimize.c says /* WARNING : As things stand, these routines should

Hi I'm trying to get the top decision rules from a decision tree. Eventually I will like to do this with R and Random Forrest. There has to be a way to output the decsion rules of each leaf node in an easily readable way. I am looking at the randomforrest and rpart packages and I dont see anything yet. Mike [[alternative HTML version deleted]]

Ok is there a way to do it with decision tree? I just need to make the decision rules. Perhaps I can pick one of the trees used with Random Forrest. I am somewhat familiar already with Random Forrest with respective to bagging and feature sampling and getting the mode from the leaf nodes and it being an ensemble technique of many trees. I am just working from the perspective that I need

Hi, I have the following matrix (named m): key sensor_date Laser_1 Laser_2 Laser_3 2010-09-30T15:00:12+0200 6 3 1 2010-10-31T15:05:07+0100 5 4 2 2011-09-30T15:00:12+0200 6

Suppose I have 100 files distributed recursively: file { "/var/sample": source => "puppet:///files/sample", ensure => directory, recurse => true } What I''d like to do is have all files inside the directory be templated: file { "/var/sample": content =>

I am trying to delete directories recursively in 'smbclient' like I typically do with 'rm -r' on a Unix shell, but I am just not able to. Is that in fact possible in 'smbclient'? Youssef Eldakar Bibliotheca Alexandrina

find duplicate filenames in a folder find | perl -ne 's!([^/]+)$!lc $1!e; print if 1 == $seen{$_}++' find duplicate filenames in a folder recursively ? how?

I am trying to create a classification tree using either tree or rpart but when it comes to plotting the results the formatting I get is different than what I see in all the tutorials. What I would like to see is the XX/XX format but all I get is a weird decimal value. I was also wondering how you know which is yes and which is no in each leaf of the tree? Is yes always on the left?

Hi, This appears to be some sort of dovecot bug. When I use the -r option to recursively delete a mailbox and sub-folders, it removes the sub-folders but not the inbox. It gives me the error below: doveadm mailbox delete -u denise at lifelinetechnique.com.au -r -s inbox doveadm(denise at lifelinetechnique.com.au): Error: Can't delete mailbox inbox: INBOX can't be deleted. Our user

Nope. Random forests are not decision trees -- they are ensembles (forests) of trees. You need to go back and read up on them so you understand how they work. The Hastie/Tibshirani/Friedman "The Elements of Statistical Learning" has a nice explanation, but I'm sure there are lots of good web resources, too. Cheers, Bert Bert Gunter "The trouble with having an open mind is