similar to: Predicting New Data -

Hi, I read data from a file. I'm trying to understand how to use Design.rcs by using simple test data first. I use 1000 integer values (1,...,1000) for x (the predictor) with some noise (x+.02*x) and I set the response variable y=x. Then, I try rcs and ols as follows: m = ( sqrt(y1) ~ ( rcs(x1,3) ) ); #I tried without sqrt also f = ols(m, data=data_train.df); print(f); [I plot original

I have ran across a case where the function isIdenticalTo is return true for instructions that are not equivalent. The instructions in question are load/store instructions, and is causing a problem with MachineBranchFolding. The problem is this, I have two branches of a switch statement that are identical, except for the size of the store. Here is some cut-down LLVM-IR to showcase the issue:

On Jan 4, 2011, at 11:08 AM, Villmow, Micah wrote: > I have ran across a case where the function isIdenticalTo is return true for instructions that are not equivalent. The instructions in question are load/store instructions, and is causing a problem with MachineBranchFolding. The problem is this, I have two branches of a switch statement that are identical, except for the size of the store.

Dear list, Given a linear mixed model (from lme4) I want to 1) first change the input dataset and then 2) change the model formula. I want this to happen in a function call; Please see below. Options 1) and 2) below work whereas 3) fails with the message > foo() Error in is.data.frame(data) : object 'beets2' not found Question: What is it one must to in case 3) to have R look

Hi, I have just set up a new dovecot server with Dovecot 2.2.5. When I create a new user and try to authenticate I get the following error Sep 03 14:33:38 imap(test2): Error: user test2: Initialization failed: Initializing mail storage from mail_location setting failed: mkdir(/home/user/apps/var/mail/imap/test2/mailboxes) failed: Permission denied (euid=503(imapd) egid=503(imapd) missing +w

Hi, My MUA (claws-mail) is having a hard time listing directories for a mail account with two namespaces, one of which using mbox and the other one using maildir to store mails. Let's call the namespaces "#mbox." and "#maildir." and have "." as separator. Assume I have the following folder hierarchy: $namespace $namespace folder $namespace folder folder1a

Is there any way to get printf type functionality inside the kernel from dtrace probes. Basically I want to dump progress through flow in my device driver. Something like: DTRACE_PRINTF("Inside chip reset, mailboxes %x %x %x %x %x %x %x %x", mb1, mb2, .....); ... ... DTRACE_PRINTF("reset failed: reason %s", failure_reasons[err]); I may have several such probes and they may

Dear all, I have just sent an email with my problem, but I think no one can see the red part, beacuse it is black. So, i am writing again the codes: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N <- 200 I <- 5 taus <- c(0.480:0.520) h <-

Hi! I recently setup a second with replication to the other. Both machines run ubuntu 12.04 with dovecot 2.2.13 (6bb26098a45c). All users mail accounts are currently synced manually to the first (mb1) using a dsync script, they are synchronised from a cyrus imap server. Users are still logging into the cyrus server. It appears that the only accounts that are replicated are ones who have

Dear All, I am analysing some data for a colleague (not my data, gotta be published so I cannot divulge). My response variable is the number of matings observed per day for some fruitlies. My factors are: Day: the observations were taken on 9 days Regime: 3 selection regimes Line: 3 replicates per selection regime. I have 81 observations in total The lines are coded A to I, so I do not need

Full_Name: Ivan the Terrible Version: 2.9.2 OS: Windows XP SP3 Submission from: (NULL) (89.110.13.151) When using the method blackboost_fit of the package mboost appear following error : Error in party:::get_variables(obj at responses) : trying to get slot "responses" from an object (class "boost_data") that is not an S4 object Simple test case that produce bug:

I'm running R 2.10.1 with mboost 2.0 in order to build predictive models . I am performing prediction on a binomial outcome, using a linear function (glmboost). However, I am running into some confusion regarding centering. (I am not aware of an mboost-specific mailing list, so if the main R list is not the right place for this topic, please let me know.) The boost_control() function allows

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

mboost contains a blackboost method to build tree-based boosting models. I tried to write my own "cost-sensitive" ada family. But obviously my understanding to implement ngradient, loss, and offset functions is not right. I would greatly appreciate if anyone can help me out, or show me how to write a cost-sensitive family, thanks! Follows are some families I wrote ngradient <-

Hi, login_log_format_elements does not seem to change the login logs. I have it set to the below setting and the word "home" does not even appear. Is there something I have to do to for this? Also I use ldap for authentication. [user at MB1 logs]$ doveconf -n | grep -i log debug_log_path = /home/user/apps/logs/dovecot_debug.log info_log_path = /home/user/apps/logs/dovecot_info.log

Sorry for the tardy reply but I just found your posting incidentally today. To make long things short: You are right about the centering. We forgot to correct the intercept if center = TRUE. We lately found the problem ourself and fixed it in the current version (mboost 2.0-3). However the problem only occurred if you extracted the coefficients. As the intercept is rarely interpretable we

Hi, I appreciate your help with the segmented function. I am relatively new to R. I followed the introduction of the 'segmented'-package by Vito Muggeo, but still it does not work. Here are the lines I wrote: data_test<-data.frame(x=c(1:10),y=c(1,1,1,1,1,2,3,4,5,6)) lr_test<-lm(y~x,data_test) seg_test<-segmented(lr_test,seg.Z~x,psi=1) /error in segmented.lm(lr_test, seg.Z ~ x,

I'm attempting to fit boosted regression trees to a censored response using IPCW weighting. I've implemented this through two libraries, mboost and gbm, which I believe should yield models that would perform comparably. This, however, is not the case - mboost performs much better. This seems odd. This issue is meaningful since the output of this regression needs to be implemented in a

_**_So I have epel enabled on this centos 6 server, but yum -y install monit will not install monit. yum search monit does not show monit as available to be installed. [root at lb1 ~]# yum install monit Loaded plugins: fastestmirror, presto Setting up Install Process Loading mirror speeds from cached hostfile * base: mirror-centos.hostingswift.com * epel: reflector.westga.edu * extras:

I'm getting started in R, and I'm trying to use one of the gradient boosting packages, mboost. I'm already installed the package with install.packages("mboost") and loaded it with library(mboost). My problem is that when I attempt to call glmboost, I get a message that " Error in glmboost() : no applicable method for "glmboost" ". Does anybody have