similar to: Linear model

I have a table statement that returns the following: [10.839,10.841] (10.841,10.843] (10.843,10.846] (10.846,10.848] (10.848,10.85] 0 0 0 0 1 (10.85,10.852] (10.852,10.854] (10.854,10.857] (10.857,10.859] (10.859,10.861] 0 0 0 0 0 What I want to do is get the upper bound

Hi, I have generated a profile likelihood for a parameter (x) and am trying to get 95% confidence limits by calculating the two points where the log likelihood (LogL) is 2 units less than the maximum LogL. I would like to do this by linear interpolation and so I have been trying to use the function approxfun which allows me to get a function to calculate LogL for any value of x within

It seems that confint.default returns an empty data.frame for objects of class mlm. For example: ``` nobs <- 20 set.seed(1234) # some fake data datf <- data.frame(x1=rnorm(nobs),x2=runif(nobs),y1=rnorm(nobs),y2=rnorm(nobs)) fitm <- lm(cbind(y1,y2) ~ x1 + x2,data=datf) confint(fitm) # returns: 2.5 % 97.5 % ``` I have seen proposed workarounds on stackoverflow and elsewhere, but

Hi everyone, I have a problem with running a glm using a subset of my data. Whenever I choose a subset, in the summary the factors arent shown (as if the variable was a continuous variable). If I dont use subsets then all the factors are shown. I have copied the output from summary for both cases. Thanks for the help, Muri > model<-glm(log(cpue)~year,family=gaussian) Call: glm(formula =

i want to ask 2 questions. 1) can R do Random-effects GLS regression which i can get from Stata? the following result is frome Stata.can I get the alike result from R? xtreg lwage educ black hisp exper expersq married union, re Random-effects GLS regression Number of obs = 4360 Group variable (i) : nr Number of groups = 545 R-sq:

Dear list, I ran a mixed effect model using R 1.4.1 and SAS 8.0 on the SIMS data found in the SASmixed package and found that the degrees of freedoms for fixed effects are very different. From R, df = n - v -1 where n is total # of observations, v is the # of levels for the grouping factor. From SAS df = v -1. Am I wrong about this or can somebody explain which is correct and why? Thanks a

Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900

Hi everyone, I'm sorry if this turns out to be more a statistical question than one specifically about R - but would greatly appreciate your advice anyway. I've been using a logistic regression model to look at the relationship between a binary outcome (say, the odds of picking n white balls from a bag containing m balls in total) and a variety of other binary parameters:

Hi: The gls function I used in my code is the following fm<-gls(y~x,correlation=corARMA(p=2) ) My question is how to extact the AR(2) parameters from "fm". The object "fm" is the following. How can I extract the correlation parameters Phi1 and Phi2 from "fm"? These two parametrs is not in the "coef" componenet of "fm". Thanks a

I've been being told, over and over, by K3B, Brasero, and Isomaster, on two machines, with three different downloads of 6.0, that the file is too large for the medium. Nautilus and the browser that die each download all say it's 4.4 GB; I've tried with two +R and an RW DVD, all of which are labelled 4.7 GB Two of the files are 32-bit, and one is 64 What is going wrong?? --

>>>>> steven pav >>>>> on Thu, 19 Jul 2018 21:51:07 -0700 writes: > It seems that confint.default returns an empty data.frame > for objects of class mlm. For example: > It seems that confint.default returns an empty data.frame for objects of > class mlm. Not quite: Note that 'mlm' objects are also 'lm' objects, and so it is

I have a data set for different time intervals. The data has three comment lines before data for each time interval. For each time interval there are 500 data points. I want to change the dataset such that I have the following format: t1 t2 t3 ................ 0.00208 0.00417 0.00625 ................. a1 a2 a3 ...................

Did something change with exception handling recently? A bunch of lit bots are showing slower compile times for many tests. Ciao, Duncan. On 20/06/12 07:53, llvm-testresults at cs.uiuc.edu wrote: > > lab-mini-03__O0-g__clang_DEV__x86_64 test results > <http://llvm.org/perf/db_default/v4/nts/1283?compare_to=1278&baseline=999> > > Run Order Start Time Duration >

< In Stata, I can just use "bs" function ...> in STATA the bs command runs a bootstrap If you want to use the bootstrap function (or you could linearize b*c/a :) look under ?boot (you may need to load the package first). Usage: boot(data, statistic, R, sim="ordinary", stype="i", strata=rep(1,n), L=NULL, m=0, weights=NULL,

Nothing that I'm aware of has changed with EH. Is it possible to bisect the problem? -bw On Jun 20, 2012, at 12:38 AM, Duncan Sands <baldrick at free.fr> wrote: > Did something change with exception handling recently? A bunch of lit bots are > showing slower compile times for many tests. > > Ciao, Duncan. > > On 20/06/12 07:53, llvm-testresults at cs.uiuc.edu

Hi Bill, > Nothing that I'm aware of has changed with EH. Is it possible to bisect the problem? I don't see any relevant LLVM changes, so I guess clang C++ compilation slowed down due to some clang changes. I'm not going to investigate this. Ciao, Duncan. > > -bw > > On Jun 20, 2012, at 12:38 AM, Duncan Sands <baldrick at free.fr> wrote: > >> Did

Dear all, I am trying to implement goodness-of-fit tests for logistic regression models described in : Hosmer, D.W., Lemeshow, S., 2000. Applied logistic regression. New-York, John Wiley & Sons, Inc., 373 p. (pp. 152-154) Namely I would like to reproduce Osius & Rojek's test (Osius, G., Rojek, D., 1992. Normal goodness-of-fit tests for multinomial models with large degrees of

On Jul 5, 2012, at 1:33 AM, Duncan Sands wrote: > Hi Bill, > >> Nothing that I'm aware of has changed with EH. Is it possible to bisect the problem? > > I don't see any relevant LLVM changes, so I guess clang C++ compilation slowed > down due to some clang changes. I'm not going to investigate this. > Crumbs. John, Do you know of anything that went into

Dear all, Does any one knows why should I get the following error message, when trying to do a simple data.frame?? DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS p,DSSp,Slope, CanDens,NearestSp) Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, : arguments imply differing number of rows: 202, 0 The data I am using