similar to: Optimization

Dear list, I'm currently trying to develop a model to assess clam yield potential in a lagoon. I'm using the zeroinfl function of the pscl package to fit a Zero-inflated negative binomial model, given the high occurrence of zero counts. I don't understand from the sentence in the pscl guide "Zero-inflated count models are a type of two-component mixture model, with a component

Dear R-list, I have a statistical problem with the comparison of two short time-series of density data in an ecological framework. I have to compare two short time series (5 years, one value for each year) of species density data (it is the density of fish in two different streams) to test if the two means of the five densities are significantly different, so basically if the two mean

Dear R-list, I have a statistical problem with the comparison of short time-series, representing densities of fish in different streams. For each stream (6 in total, here below showed only part of the dataset) I have 8 years of density data, as follows: year density stream 1 2000 0.51 stream1 2 2001 0.87 stream1 3 2002 0.68 stream1 4 2003 0.56 stream1 5 2004 0.50 stream1 6

Hallo, yesterday I was puzzled when I discovered that I probabliy miss something in the interepretation of intercept in two-way lm models. I thought that the intercept, using the default contr.treatment contrasts, represents the mean of the group of observations having zero in all column of the model.matrix. It turns out not to be case To be more more clear I am attaching a short example:

Hallo, I have a question that is more statistic related than about nlme and R functioning. I want to fit a complicated nonlinear model with nlme with several different measures of transpiration taken on each of the 220 trees grouped in 8 families. The unknown parameters of the model are three + their variances (and covariances). I want to estimate the variances among families of the

Hi all, I'm trying to use the PPL (Parma Polyhedra Library, bugseng.com/products/ppl) in one of my LLVM passes getting the error: > Error opening > '/home/jorge/SvnReps/Systems/llvm/build/Debug+Asserts/lib/MyAnalysis.so': > /home/jorge/SvnReps/Systems/llvm/build/Debug+Asserts/lib/MyAnalysis.so: > undefined symbol: _ZNK23Parma_Polyhedra_Library13PIP_Tree_Node2OKEv >

[[diverted from R-bugs to R-help by the list maintainer]] Dear Friend and distinguished R gurus, first of all really thank you very much for the marvellous tool that is R. I am using R 2.5.0, windows XP - italian language. I was perfoming some calculation on fractional exponential and I found a strange behaviour. I do not know if it is really a bug, but I would expect a different answer from

I keep getting the 'memory.size' error message when I run a program I have been writing. It always it cannot allocate a vector of a certain size. I believe the error comes in the code fragement below where I have multiple arrays that could be taking up space. Does anyone know a good way around this? w1 <- outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 <- outer(xk$xk2,

Hi Jorge, > I'm trying to use the PPL (Parma Polyhedra Library, > bugseng.com/products/ppl) in one of my LLVM passes getting the error: > >> Error opening >> '/home/jorge/SvnReps/Systems/llvm/build/Debug+Asserts/lib/MyAnalysis.so': >> /home/jorge/SvnReps/Systems/llvm/build/Debug+Asserts/lib/MyAnalysis.so: >> undefined symbol:

Dear R Helpers, I have noticed that when I use lmer to analyse data, the summary function gives different values for the AIC, BIC and log-likelihood compared with the anova function. Here is a sample program #make some data set.seed(1); datx=data.frame(array(runif(720),c(240,3),dimnames=list(NULL,c('x1','x2','y' )))) id=rep(1:120,2); datx=cbind(id,datx) #give x1 a

useR's, I am trying trying to find out if there is a faster way to do a certain computation. I have successfully used FOR loops and the apply function to do this, but it can take some time to fully compute, but I was wondering if anyone may know of a different function or way to do this: > x [1] 1 2 3 4 5 > xk [1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 I want to do:

Consider a data frame (x) with 2 variables, x1 and x2, having equal values. It looks like: x1 x2 1 1 2 2 3 3 Now, consider a second data frame (xk): xk1 xk2 0.5 0.5 1.0 0.5 1.5 0.5 2.0 0.5 0.5 1 1.0 1 1.5 1 2.0 1 0.5 1.5 1.0 1.5 1.5 1.5 2.0 1.5 0.5 2 1.0 2 1.5 2 2.0 2 I have written code to calculate some differences between these

Hello dear R help members. I am trying to understand the anova.rq, and I am finding something which I can not explain (is it a bug?!): The example is for when we have 3 nested models. I run the anova once on the two models, and again on the three models. I expect that the p.value for the comparison of model 1 and model 2 would remain the same, whether or not I add a third model to be compared

R 2.8.1 Windows XP I am trying to plot the results of a coxph using plot(survfit()). The plot should, I believe, show two lines one for survival in each of two treatment (Drug) groups, however my plot shows only one line. What am I doing wrong? My code is reproduced below, my figure is attached to this EMail message. John > #Create simple survival object >

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >

On Tuesday, November 15, 2011 at 10:11:25 (+0100), Duncan Sands wrote: >> Hi Jorge, >> >> > I'm trying to use the PPL (Parma Polyhedra Library, >> > bugseng.com/products/ppl) in one of my LLVM passes getting the error: >> > >> >> Error opening >> >> '/home/jorge/SvnReps/Systems/llvm/build/Debug+Asserts/lib/MyAnalysis.so':

Dear all, I have discovered that there are many things that I used to do in my GIS which are easily done directly in R, for example calculating interpoint distances using geoR and pick out points inside a polygon using splancs. I now wonder, is there a function to create a line object like a watercourse and then calculate the distances between many points in space and this line? I couldn't

I am trying to find methods for testing and visualizing calibration to Cox models with time-depended coefficients. I have read this nice article <http://journals.sagepub.com/doi/10.1177/0962280213497434>. In this paper, we can fit three models: fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0) p <- log(predict(fit0, newdata = data1, type = "expected")) lp

Hi , I want to apply the following code fo my data with 400 predictors. I was wondering if there ia an alternative way instead of typing 400 predictors for the following code. I really appreciate your help. fit0<-lm(Y~1, data= mydata) fit.final<- lm(Y~X1+X2+X3+.....+X400, data=mydata) ??? step(fit0, scope=list(lower=fit0, upper=fit.final), data=mydata, direction="forward")

First, as others have said please obey the mailing list rules and turn of First, as others have said please obey the mailing list rules and turn off html, not everyone uses an html email client. Here is your code, formatted and with line numbers added. I also fixed one error: "y" should be "status". 1. fit0 <- coxph(Surv(futime, status) ~ x1 + x2 + x3, data = data0) 2. p