similar to: logical(0) response from lrm

Is there a cleaner way of combining two expressions. This example works and gives what I want plot(1:10) aa <- expression(alpha==.05) bb <- expression(beta ==.80) aabb <- expression(alpha==.05 ~ ", " ~ beta ==.80) text(5, 10, aa) text(5, 9, bb) text(5, 8, aabb) text(5,1, parse(text=paste(deparse(aa[[1]]), deparse(bb[[1]]), sep="~"))) text(5,2,

Good evening, I understand that NTFS & VMDK do not relate to Solaris or ZFS, but I was wondering if anyone has any experience of checking the alignment of data blocks through that stack? I have a VMware ESX 4.0 host using storage presented over NFS from ZFS filesystems (recordsize 4KB). Within virtual machine VMDK files, I have formatted NTFS filesystems, block size 4KB. Dedup is turned on.

On 23/11/2014 09:39, peter dalgaard wrote: > >> On 23 Nov 2014, at 01:05 , Henrik Bengtsson <hb at biostat.ucsf.edu> wrote: >> >> On Sat, Nov 22, 2014 at 12:42 PM, Duncan Murdoch >> <murdoch.duncan at gmail.com> wrote: >>> On 22/11/2014, 2:59 PM, Stuart Ambler wrote: >>>> A colleague?s R program behaved differently when I ran it, and we

on Fri Jul 28 14:30:33 2023 Rowland Penny via samba <samba at lists.samba.org> wrote: > On 28/07/2023 19:04, Mark Foley via samba wrote: > > > > After checking with the previous run, these sysvolreset errors are the same as > > before, so syncing the sysvol didn't make any different. > > > > You wrote: "It looks to me that you have more GPO's

Dear list! > gregexpr("a+(b+)", "abcdaabbc") [[1]] [1] 1 5 attr(,"match.length") [1] 2 4 What I want is the offsets of the matches for the group (b+), i.e. 2 and 7, not the offsets of the complete matches. Is there a way in R to get that? I know about gsubgn and strapply, but they only give me the strings matched by groups not their offsets. I could write

Dear all, I have invested substantial amount of work in a complicated, yet on screen perfect looking graph that uses image(). Unfortunately saving it as pdf (or quartz.save at high resolution) all generate very disturbing border lines around each small rectangle that image() has drawn. While using Preview it helps to turn off antialiasing to make those faint lines disappear on screen

Hello, I get last_login_dict: Failed to write value: dict-server returned failure: sql dict: commit failed randomly in the logs: --- ???????1 mailserver dovecot: imap(test-email-bb at exemple.com) <NtiT9H2SFIVcuGID> [xxx.xxx.xxx.xxx]: Error: last_login_dict: Failed to write value: dict-server returned failure: sql dict: commit failed: INSERT, UPDATE command denied to user

Hello I'm using logistic regression from the Design library (lrm), then fastbw to undertake a backward selection and create a reduced model, before trying to make predictions against an independent set of data using predict.lrm with the reduced model. I wouldn't normally use this method, but I'm contrasting the results with an AIC/MMI approach. The script contains: # Determine full

Hi R-helpers I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ..., clust) containing relatively many NAs. When I fit an ordinal regression model with the function lrm from the Design library: model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE) it will by default delete missing values in the variables y, x1, x2. Based on model.lrm, I want to apply the robust covariance

> On Sep 14, 2017, at 12:30 AM, Bonnett, Laura <L.J.Bonnett at liverpool.ac.uk> wrote: > > Dear all, > > I am using the publically available GustoW dataset. The exact version I am using is available here: https://drive.google.com/open?id=0B4oZ2TQA0PAoUm85UzBFNjZ0Ulk > > I would like to produce a nomogram for 5 covariates - AGE, HYP, KILLIP, HRT and ANT. I have

Hi, I am running a logistic regression model using lrm library and I get the following error when I run the command: mod1 <- lrm(death ~ factor(score), x=T, y=T, data = env1) Unable to fit model using ?lrm.fit? where score is a numeric variable from 0 to 6. LRM executes fine for the following commands: mod1 <- lrm(death ~ score, x=T, y=T, data = env1) mod1<- lrm(death ~

Hi there! I've a couple of questions on -R feature: Here is my situation: PC_A has a private IP, ssh client and has a service I want to see from the internet. PC_B is a linux firewall (public IP) where there is an open port that forwards all traffic to PC_C (ssh server on port 22) which is in PC_B LAN. I want to create a tunnel from PC_A to PC_C to access a service on PC_A from

Fixed 'maxiter' in the help file. Thanks. Please give the original source of that dataset. That dataset is a tiny sample of GUSTO-I and not large enough to fit this model very reliably. A nomogram using the full dataset (not publicly available to my knowledge) is already available in http://biostat.mc.vanderbilt.edu/tmp/bbr.pdf Use lrm, not lrm.fit for this. Adding maxit=20 will

Hello everybody, I am trying to do a logistic regression model with lrm() from the design package. I am comparing to groups with different medical outcome which can either be "good" or "bad". In the help file it says that lrm codes al responses to 0,1,2,3, etc. internally and does so in alphabetical order. I would guess this means bad=0 and good=1. My question: I am trying to

Hi, I have to build a logistic regression model on a data set that I have. I have three input variables (x1, x2, x3) and one output variable (y). The syntax of lrm function looks like this lrm(formula, data, subset, na.action=na.delete, method="lrm.fit", model=FALSE, x=FALSE, y=FALSE, linear.predictors=TRUE, se.fit=FALSE, penalty=0, penalty.matrix, tol=1e-7,

Dear all, I am using the publically available GustoW dataset. The exact version I am using is available here: https://drive.google.com/open?id=0B4oZ2TQA0PAoUm85UzBFNjZ0Ulk I would like to produce a nomogram for 5 covariates - AGE, HYP, KILLIP, HRT and ANT. I have successfully fitted a logistic regression model using the "glm" function as shown below. library(rms) gusto <-

Hi R helpers, I'm fitting large number of single factor logistic regression models as a way to immediatly discard factor which are insignificant. Everything works fine expect that for some factors I get error message "Singular information matrix in lrm.fit" which breaks whole execution loop... how to make LRM not to throw this error and simply skip factors with singularity

Hi R, I am getting this error while trying to use 'lrm' function with nine independent variables: > res = lrm(y1994~WC08301+WC08376+WC08316+WC08311+WC01001+WC08221+WC08106+WC0810 1+WC08231,data=y) singular information matrix in lrm.fit (rank= 8 ). Offending variable(s): WC08101 WC08221 Error in j:(j + params[i] - 1) : NA/NaN argument Now, if I take choose only four

Hi, I've come across a strange error when using the lrm.fit function and the subsequent predict function. The model is created very quickly and can be verified by printing it on the console. Everything looks good. (In fact, the performance measures are rather nice.) Then, I want to use the model to predict some values. I get the following error: "fit was not created by a Design

I am trying to obtain the AICc after performing logistic regression using the Design package. For simplicity, I'll talk about the AIC. I tried building a model with lrm, and then calculating the AIC as follows: likelihood.ratio <- unname(lrm(succeeded~var1+var2,data=scenario,x=T,y=T)$stats["Model L.R."]) #Model likelihood ratio??? model.params <- 2 #Num params in my model AIC