similar to: Linear models and a simple time series

Dear all, I am trying to use R to fit mixed models. Take the following example, where ind is a random effect and sample is fixed. I wanted to fit Model 1: values = ind + sample Model 2: values =ind * sample Model 3: values=ind(sample) + sample Tried to use the below for mod1, but it did not work. Can anyone give some help on this. Thanks so much. mod1 <- lme(values ~ sample +

Dear all, I have a question on applying a function to the data according to factor levels. For example, for the data below, what is the best way to apply a function to "values" according to different levels of "samples" (1,2,3,4,5)? values ind sample 1 0.03325 1 1 2 0.03305 1 1 3 0.03185 1 1 4 0.03515 1 1 5 0.03375 1 1 6 0.01180

Preparing a paper for a medical journal. Using the prop.test() function in R (v2.4.0) to compare two groups' response to data like the following. A sample of 100 individuals from Population I, 18 with positive readings from a certain test, vs. A sample of 148 individuals from Population II, 61 with positive readings. Results look like this: R version 2.4.0 Patched (2006-11-25

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

Working with a number of scripts (text files with R commands) that I "source" into R sessions from time to time. The source() command is most convenient (at least for me) if it only loads function definitions, and doesn't otherwise change the interactive environment. For example, I might have a file that looks like func1<-function() { code code code } # this

hello, I work since a few time on R and i wanted to know how to obtain the Wald chi square value when you make a binary logistic regression. In fact, i have the z value and the signification but is there a script to see what is the value of Wald chi square. You can see my model below, Best regards, S??verine Erhel [Previously saved workspace restored] > m3 = glm(reponse2 ~ form +

Dear List: Below is the validation output of a fitted ordinal logistic model using the bootstrap in the rms package. My interpretation is that most of the corrected indices indicate little overfitting, however the slope seems to indicate that the model is too optimistic. Given that most of the corrected indices seem reasonable, would it be appropriate to use this model on future data if the

Greetings R users, maybe there is someone who can help me with this problem: I'm trying to fit this discontinous model : GE<-data.frame( Ci<-c(81,87,91,111,159,173,295,453,629,984), A<-c(-0.9,1.2,3.5,8.3,13.1,14.4,22.9,27.3,29.6,32.6) ) rhs <- function(Ci, Vcmax, J, Rd) { ? ?R <-0.008314472 ? ?Tleaf <-25 ? ?Kc <-exp(38.05-79.43/(R*(Tleaf+273.15))) ? ?Ko

An organization has asked me to comment on the validity of their recent all-employee survey. Survey responses, by geographic region, compared with the total number of employees in each region, were as follows: > ByRegion All.Employees Survey.Respondents Region_1 735 142 Region_2 500 83 Region_3 897 78

Dear all: I converted the columns (Baci, Meti, Fungii, Protozoai) into integers (using excel) and then imported the data (.txt) into R. Interestingly, the other three variables were loaded as INT, but the 'Baci' one continued as Num. I imported the data using the following command line: X <- read.delim(file.choose(), header = TRUE, dec =

Hello! I'm puzzled by the following problem. It occurs while trying to predict responses in a test-dataset using a linear model fitted with regFit from the rMetrics "fRegression"-package. All goes well when I call "predict" using the training dataset. However, a call using the test-dataset retuns an error message - telling me that the latter dataset provides variables

Hello!   I estimate vector error correction model (vecm) model. I have only one cointegratio relationship. I write :   joh.vecm.rls <- cajorls(joh.vecm, r=1) The output estimation is : Call: lm(formula = substitute(form1), data = data.mat) Coefficients:                up.d            expl.d        upd.d           r.d      ect1      -1.34e-01   4.55e+02   6.91e+00   2.43e+03 constant 

Hi, I have a question about using "lme" and "aov" for the following dataset. If I understand correctly, using "aov" with Error term in the formula is equivalent to using "lme" with default settings, i.e. both assume compound symmetry correlation structure. And I have found that equivalency in the past. However, with the follwing dataset, I got different

Hi, I have a question about using "lme" and "aov" for the following dataset. If I understand correctly, using "aov" with an Error term in the formula is equivalent to using "lme" with default settings, i.e. both assume compound symmetry correlation structure. And I have found that equivalency in the past. However, with the follwing dataset, I got different

Hi all, Sent the following question yesterday, but haven't got any suggestions yet. So just trying again, can anyone comment on the problem that I have? Thank you! ------------- Hi, I have a question about using "lme" and "aov" for the following dataset. If I understand correctly, using "aov" with an Error term in the formula is equivalent to using

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

Hi Bert, Thanks for the suggestions. I tried lme with different control parameters, and also tried using "ML", instaed of "REML", but still got the same answers. Yes, I hope some gurus on this list could give me some hints. Thanks --- "Gunter, Bert" <bert_gunter at merck.com> wrote: > But they are close. This is almost certainly a > numeric issue --

Ok. I`m trying to run a Poisson glmm with an observation-level random intercept. But I`m getting the following error for the 'Baci' variable: 'Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate'. I guess this message is because the baci variable is not a an integer, and cannot be transformed into an integer as R has a threshold of 2x10^9 even in

Hi All, I have a strange problem that I don't understand. I have an access file which has the following line: 168.144.250.215 OK # xsmtp02.mail2web.com Yet email from this IP address is getting rejected. From my log file Oct 15 21:52:33 mx01 sendmail[10569]: ruleset=check_relay, arg1=xsmtp02.mail2web.com, arg2=168.144.250.215, relay=xsmtp02.mail2web.com

Thx Rudi, I tried but the mirrors citrix and citrix/primary give error : no package make available. Not sure if I can configure another download server. Harry Original Message: ----------------- From: Rudi Ahlers Rudi@SoftDux.com Date: Fri, 29 Oct 2010 16:52:29 +0200 To: harry@aasterud.com, xen-users@lists.xensource.com Subject: Re: [Xen-users] In the process of deciding to