similar to: Standardized residual variances in SEM

I currently have a data frame whose rows correspond to each student and whose columns are different variables for the student, as shown below: Lastname Firstname CATALOG_NBR Email StudentID EMPLID Start 1 alastname afirstname 1213 *@uark.edu 10295236 # 12/2/2008 2 anotherlastname anotherfirstname 1213 **@uark.edu ## 10295236 9/3/2008 Xattempts Q1

I am fairly new to R and would like help with the problem below. I am trying to sum and count several rows in the data frame yy below. All works well as in example 1. When I try to add the columns, with an NA in Q21, I get as NA as mySum. I would like NA to be treated as O, or igored. I wrote a function to try to count an NA element as 0, Example 3 function. It works with a few warnings,

hi dovecot: when i login 100 users with imap protocol ,Someusers appeared a BUG in maillog like : Sep 10 09:05:22 auth(default): Error: BUG: Worker sent reply with id 393, expected 394 Sep 10 09:05:22 auth(default): Error: worker-server(q82 at t.com,10.12.80.3): Aborted: Worker is buggy Sep 10 09:05:22 auth(default): Error: BUG: Worker sent reply with id 31, expected 32 Sep 10 09:05:22

Hello, I have a problem with a Grandstream being behind a symmetric nat. The box which does the nat is a german "Fritz Box". This one does nat for the internal network. In the internal network is a Granstream BudgeTone 100. The nat router has a dial-up connection, so ip changes on every dial-in. |------------| |------------| |--------| |Grandstream

R Experts, I have a dataframe made up of character vectors--these are results from survey questions. I need to convert them to factors. I tried the following which did not work: scs2<-sapply(scs2,as.factor) also this didn't work: scs2<-sapply(scs2,function(x) as.factor(x)) After doing either of above I end up with >str(scs2) chr [1:10, 1:10] "very important" "very

Hello R-users, I have been trying to fit what I think is a simple mixed-effects model using lmer (from lme4), but I've run into some difficulty that I have not been able to resolve using the existing archives or Pinheiro and Bates (2000). I am measuring populations (of birds) which change with time at a number of different sites. These sites are grouped into regions. Sites are not measured

Hi everybody, I'm trying to fit a Garch(1,1) process to the DAX returns. My data consists of about 2300 10day-logreturns in chronologically descending order (see attachment). But if I use the garch function I get a very high alpha_1 and a quite low beta, which doesn't make that much sense. I think I am missing something, but have no idea what it might be. I'd appreciate it a lot

Hi, I'm trying to create a plot showing the density distribution of some shipping data. I like the look of violin plots, but my data is not continuous but rather binned and I want to make sure its binned nature (not smooth) is apparent in the final plot. So for example, I have the number of individuals per vessel, but rather than having the actual number of individuals I have data in the

Dear experts, I'm attempting to solve a constrained optimization problem using the Rdonlp2 package. I created a Lagrange function (L=f(x)-lambda(g(x)-c)), where x is a vector of 16 parameters. This is what I'm using as objective function in the code below. In addition, I set bounds on these parameters (par.u and par.l). When I run the code, I get the error message shown below. Any idea

Full_Name: Gang Liang Version: 1.4.1 OS: mandrake-8.2 Submission from: (NULL) (128.32.81.135) tseries version: 0.9-1 quadprog version: 1.4-4 mva version: 1.4.1 version: platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 4.1 year 2002 month 01

On 20/11/2017 6:38 AM, Maria Lathouri via R-help wrote: > Dear all > I know that it is a very simple question but it seems that I cannot change the colour in the bars. > I have the following dataframe: > A ? ? ? ? ? ? ? ?? B ? ? ? ? ? ? ? ? C ? ? ? ? ? D ? ? ? ?? E ? ? ? ? ? ? ? ? ?? F ? ? ? ? ? ? ? ? ?? G ? ? ? ? ? ? ? ?0.0.24 ? ? ? ?? 152460 ? ? ? ? 474 ? ? ? 5.5 ? ? ?? 612000 ? ?

The following fit does not make sense to me, please, correct me if I have a logical error. > moddowsn Call: coxph(formula = Surv(start, stop, resp) ~ sn + matfac2, data = coxsn1, method = "efron") coef exp(coef) se(coef) z p sn2 0.0497 1.051 0.02030 2.450 1.4e-02 sn3 -0.0532 0.948 0.02038 -2.610 9.0e-03 sn4 -0.0410 0.960

On 20/11/2017 7:09 AM, Maria Lathouri wrote: > Dear all, > > I am really sorry for this. I have attached the script and a .csv file > with an example. The problem is that you have dat as a matrix with only one row. barplot() applies the colours to the rows of dat; since you have only one row, everything ends up blue. You can fix this by creating dat as a vector using

Hello, I am hoping for some advice regarding warning/error messages I received when running a Cox regression # message 1 - obtained while creating a plot of residuals > plot (NV.zph, main = "groupNUSM - UNFIT", var= 'groupNUSM') Warning messages: 1: In approx(xx, xtime, seq(min(xx), max(xx), length.out = 17)[2 * : collapsing to unique 'x' values 2: In

I have a model with quant vars only and the error message does not make sense: (mod1 <- coxph(Surv(time=strt,time2=stp,event=(resp==1))~ +incpost+I(amt/1e5)+rate+strata(termfac), subset=dt<"2010-08-30", data=inc,method="efron")) Call: coxph(formula = Surv(time = strt, time2 = stp, event = (resp == 1)) ~ +incpost + I(amt/1e+05) + rate + strata(termfac),

Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add

Dear all,? I am really sorry for this. I have attached the script and a .csv file with an example.? Hope this will help. Many thanks,Maria ???? 11:53 ?.?. ???????, 20 ????????? 2017, ?/? Duncan Murdoch <murdoch.duncan at gmail.com> ??????: On 20/11/2017 6:38 AM, Maria Lathouri via R-help wrote: >? Dear all > I know that it is a very simple question but it seems that I cannot

I am trying to use the survfit() function with the newdata argument to produce predicted survivor curves for a particular covariate profile. The main purpose of the plot will be to visualise the effect of snp1, coded 0 and 1. In my Cox model I have stratified by one variable, edu, and so I know I will automatically get a separate curve for each strata. My problem is how to deal with the

Dear R users: I am using survreg for modeling left censored longitudinal data. When I am using the following code for fitting the tobit model I am getting some output with an warning message(highlighted with red color): > survreg(Surv(y, y>=0, type='left')~x + frailty(id), cytokine.data, weight=w, dist='gaussian', scale=1) Call: survreg(formula = Surv(y, y >= 0, type

Hi there, Can anyone please help me because I am going to get crazy with the pbc data set. I just want to apply simple cox regression in the data set. I am a beginner in R but I don't think I am doing anything wrong. I have the book of Fleming and Harrington 1990. I perform cox regression by typing: out<- coxph(Surv(times/365,status)~log(bili)+log(proth)+edema+log(albumin)+age) out