similar to: r-help@stat.math.ethz.ch

Dear: Continuing the issue of 'ifelse'! I selecting the data whose 'x2'=1 for maximizing likelihood. I used two way to do this but the results are different. 1.Way one I use the data for x2=1 and run the program. It works for me. Tthe program is described as below: function (parameters,y1,x11) { p<-parameters[1] alpha1<-parameters[2] beta1<-parameters[3]

Dear: I try to revise the maximum likelihood function below using something constrains. But it seems something wrong with it. Becasue R would not allow me to edit the function like this. It is very appreciate if you can help. function (parameters,y,x1,x2) { p<-parameters[1] alpha1<-parameters[2] beta1<-parameters[3)] delta1<-parameters[4] alpha2<-parameters[5]

Dear All: I used optim() to minimise the loglikelihood function for fitting data to negative binomial distribution. But there initial value of log-likelihood and iteration 10 value are reasonable. for example: initial value 1451657.994524 iter 10 value 47297.534905 iter 20 value -623478636.8236478 Then the iter 20 vlaue suddelnly changes to a negative value and in the end the error mesage is

doh-trying again- this time remember text only. Hello all- I am having trouble with the cell sizes that heatmap defaults too. I have a matrix of 160 rows and 5 columns that I am trying to display with heatmap(). When I do this, the cells default to really wide and very short. This makes the labels for the rows very hard to read, in fact the only way I can read them is to make the jpeg output

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Hi all, I have been trying to get to the ftp site to download the R patched tarball and cannot seem to get to it today. I have tried via browser, gFTP and get without success. I can seem to do an anonymous login, but that is as far as I can go. Is there a known issue with the site today? Thanks, Marc

lgamma(x) and lfactorial(x) are defined to return ln|Gamma(x)| {= log(abs(gamma(x)))} or ln|Gamma(x+1)| respectively. Unfortunately, we haven't chosen the analogous definition for lchoose(). So, currently > lchoose(1/2, 1:10) [1] -0.6931472 -2.0794415 NaN -3.2425924 NaN -3.8869494 [7] NaN -4.3357508 NaN -4.6805913 Warning message: In

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As many of you have probably realized, the spam filtering at @stat.math.ethz.ch has been dead for since yesterday (09-25) ~16:50 till today ~08:30. The sudden death may have been caused by unrelated installation of some perl modules (spamassassin *is* running on perl) by our IT staff. We are very sorry for this event. On the bright side: You have been able to get a glimpse of what you are

Hi, I have a bivariate longitudinal dataset. As an example say, i have the data frame with column names var1 var2 Unit time trt (trt represents the treatment) Now suppose I want to fit a joint model of the form for the *i* th unit var1jk = alpha1 + beta1*timejk + gamma1* trtjk + delta1* timejk:trtjk + error1jk var2 = alpha2 + beta2*timejk + gamma2* trtjk + delta2* timejk:trtjk +

I have a complex function that I want to maximize (I have multiplied this function by -1 so that it becomes a minimization problem in the code below). This function has two equality constraints. I get the programs to run but the answer isn't correct because, when it does converge, at least one of the constraints is violated. Any suggestions? Code below Violated constraint (an easy check):

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Hi r-users;   I have this values: eign_val <- c(137.810447,3.538721,2.995161,1.685670) alp    <- 1.6549 ;  lamda <- eign_val lamda_m <- min(lamda)   First I calculated manually: delta0 <- 1 delta1 <- alp*delta0*(4-lamda_m*(1/lamda[1]+1/lamda[2]+1/lamda[3]+1/lamda[4]))  delta1 delta2 <- (alp/2)*(delta1*(delta1/alp) + delta0*((1-lamda_m/lamda[1])^2+

a graph question. Thanks a lot in advance. I made two scatterplots on one graph (sigma vs. delta1, sigma vs. delta2) (20 observations of delta1, delta2 and corresponding sigma) the x-axis is sigma, the y-axis is either delta1 or delta2. I connected both scatterplots. To seperate them, one curves is a line with circles, the other curve is a line with squares on it. I want to make a notation

Dear R community, I have trouble implementing a nested variance-covariance matrix in the lme function. The model has two fixed effects called End and logpgc, the response variable is the logarithm to base 2 of Intensity ( log2(Intensity) ) and the random effects are called Probe and ProbeNo. The model has the following nesting structure: A Pixel is nested within the ProbeNo,the ProbeNo is

Dear all, I tried running the following syntax but it keeps running for about 4 hours and then i got the following errors: Error in if (is.na(f0$objective)) { : argument is of length zero In addition: Warning message: In is.na(f0$objective) : is.na() applied to non-(list or vector) of type 'NULL' Here is the syntax itself: library('nloptr') library('pracma') #

Hi, I'm getting an error message using polr(): Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) : initial value in 'vmmin' is not finite The outcome variable is ordinal and factored, and the independant variable is continuous. I've checked the source code for both polr() and optim() and can't find any variable called

Dear listers, Am currently using MCMC approaches to estimate some parameters of my model. One parameter has to be updated using a tuned gamma distribution. So at each iteration I estimate the mean and variance of the density of the gamma approximation using "vmmin" (i also supply the gradient argument). For moderate replications the procedure works, but if I increase them R crashes.

I'm solving 4 complex equations simultaneously. Code is below. The code returns only zero's for the solution though there should also be a non-zero result. I'm pretty confident that the equations are correct because they are straight from a published paper and I checked them pretty thoroughly. The parameter values I used are from the published paper as well. Any suggestions for how

Dear: I want to plot barplot and let bar be in the middle of each x axis category. Do you have this experience? Many Thanks! Xin [[alternative HTML version deleted]]