similar to: extract variables from linear model

Hi, The question is as follows: has anyone coded panel data unit root tests with R? Even the "first generation" tests (see e.g. Levin & Lin 1993; Pesaran, & Smith & Im 1996; Maddala & Wu 1999) would be sufficient for my needs. To my understanding, these are rather easy to code, but as I have taken just my first steps in coding with R, existing code would save me

When finally got some time to do some coding, I started and stopped right after. The stationary test is a good starting point because it demonstrates how we should be able to move the very basic R matrices. I have a real- world small N data set with rows: id(n=1)---t1---variable1 ... id=(N=20)---T=21---variable1 Thus, a good test case. For first id I was considering something like this: lag

Does lme prediction work correctly with poly() terms? In the following simulated example, the predictions are wildly off. Or am I doing something daft? Milk yield for five cows is measured weekly for 45 weeks. Yield is simulated as cubic function of weekno + random cow effect (on intercept) + residual error. I want to recover an estimate of the fixed curve. ############### library(nlme)

Is there an existing function to compute Cook-Weisberg confidence curves for non-linear model parameters in R? Kari Ruohonen -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !)

Hi, this is possibly a FAQ, but I couldn't find an answer to it so far, neither in the "Official HOWTO" nor somewhere else. Does Samba have native Kerberos V support, i.e. is it possible to authenticate against a (Heimdal, in our case) kdc? Hints are appreciated! TIA, Jukka -- bashian roulette: $ ((RANDOM%6)) || rm -rf ~

Hi, I wonder if there is a possibility to avoid that R sets one level of a factor equal zero in a model fit. More precisely, I want to fit a two-way unbalanced linear model: o ~ 0 + x + y x is a factor with 10 levels, y is a factor with 9 levels. In order to get a unique solution i set the intercept =0 and impose that sum(y)=0 i.e. res <- lm(o ~ 0 + x + y,

Hello all, I was asked to bring attention to this LLVM ticket to the mailing list: https://bugs.llvm.org/show_bug.cgi?id=46201 - Missing LLVM NOTICE file is making redistributing LLVM difficult. It was recently noted by our legal review in release management that LLVM third-party licenses are scattered over different files, which complicates faithful license-preserving redistribution of LLVM to

Hello, Hope that someone could help me plotting longitudinal data below: 7213 3333330001 0.8300 13.05.09 1 1 3333330001 0.8700 09.02.05 NULL 4797 3333330001 0.7700 21.03.07 NULL 2399 3333330001 0.7800 12.04.06 NULL 2400 3333330002 NULL 27.03.06 NULL 7230 3333330002 0.8200 14.05.09 0 2 3333330002 0.8400 09.02.05 NULL 4798 3333330002 0.8700 20.03.07 0 4799 3333330003 0.9000 20.03.07 13 2401

Hi, I would appreciate of someone could explain how the residual standard error is computed for rlm models (MASS package). Usually, one would expect to get the residual standard error by > sqrt(sum((y-fitted(fm))^2)/(n-2)) where y is the response, fm a linear model with an intercept and slope for x and n the number of observations. This does not seem to work for rlm models and I am wondering

Hi, I wonder if predict.gam is supposed to work with family=negbin() definition? It seems to me that the values returned by type="response" are far off the observed values. Here is an example output from the negbin examples: > set.seed(3) > n<-400 > dat<-gamSim(1,n=n) > g<-exp(dat$f/5) > dat$y<-rnbinom(g,size=3,mu=g) >

Hello, Could somebody please tell me what am I doing wrong in following? I try extract coefficients (using arm-package) from the lmer frunction, but I get the following warning: a<-data.frame(coef(res)) Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : cannot coerce class "coef.mer" into a data.fram I think I have done it before

Hi! I'm a bit new to Samba+LDAP integration, and most likely because of that I experienced this morning something I can't fully understand. I would appreciate if someone could explain to me what was really wrong. So, our name server was unavailable this morning due to OS update. Division's Samba and LDAP services are running on same server, and Samba is using TLS in connecting to

I am trying to explore nlmer by running some nlme examples from Pinheiro & Bates (2000). I do not seem to find information how to specify fixed effects covariates to nlmer models. Specifically, I tried to run the "Carbon Dioxide Uptake" example from p. 368 onwards in the PB200 book. The model without fixed effects covariates runs well but how to tell nlmer to include Type and

Hello,   I am trying to calculate predicted values derived from one dataset into a hypothetical dataset. I tried this line of code:   graphdata$fmgpredvalues <- predict(Acs250.3.4, graphdata)   and received the following error message:   ERROR: ZXend[1], drop = FALSE] %*%lmeFit$beta   I have made sure all variable names are the same between the two datasets and all factors are appropriately

Hi, I wonder if someone could help. I needed to transfer (copy) a workspace file that had been generated in linux (R 2.11) to windows running the same version of R 2.11 (but of course windows binary). Usually, there is no problem in doing this and all objects work as expected. I am often doing this to be able to produce wmf or emf graphic files that I need. This time I had some spectra that I

This is maybe not directly an R problem but I have used R to try to solve it so I think somebody may be able to help. I have a mixture model with three components and a quadratic Scheffe polynomial p1x1+p2x2+p3x3+p12x1x2+p13x1x3+p23x2x3 fitted to the response. Now I'd like to compute the mixture corresponding the maximum response. Model for Y1 has the parameters p1=124.02 p2=60.973 p3=41.479

Greetings, Are there any plans to import SCTP support to OpenSSH? There have been SCTP patches for OSX and FreeBSD, and those seem to work pretty decently. I guess there might quite a number of potential users for SCTP were it part of the common source tree. A second benefit of having SCTP support as a standard feature in OpenSSH for all platforms supporting SCTP would be kind of social pressure

Hi, I have faced a problem with the merge() function when trying to merge two data frames that have a common index but the second one does not have cases for all indexes in the first one. With usual variables R fills in the missing cases with NA if all=T is requested. But if the variable is a matrix R seems to insert NA only to the first column of the matrix and fill in the rest of the columns by

Hi, I have a linear mixed-effects model object and want to extract the 95% confidence intervals for the fixed and random effects, respectively. I found the function intervals() for confidence intervals for the fixed effects but no corresponding function for the random effects. Does it exist or do I have to calculate the confidence intervals for the random effects myself? Greetings, joerg

Hi, does anybody know of a nice test to detect trend turning points in time series? Possibly with reference? Thanks, joerg