similar to: optimisation procedure with flat log-likelihood

Dear R-users, I am going to try to be as clearer as possible, showing also an example. 1) I have a function (in my real case it's much more complex) 2) I use "optim" to minimize 3) I want to use as method L-BFGS-B for several reasons 4) I know I could use "trace=6" (in "control") in order to see "live" the procedure 5) I would like to see separately the

Dear R-users, within the rgl-package, I would have a question about the usage of persp3d in combination of rgl.viewpoint. I am not able to figure out how to let a 3D plot rotating around likewise the example in ?rgl.viewpoint. It seems that when I use persp3d(...) I see something on my screen, which is different from what I get when it's rotating. Is there any different behavior between

Dear R-users, I would like to place two 3D plots side-by-side in a rgl-setting. It would nice to have something like "par(mfrow=c(1,2))" for basic plots, or an array framework for wireframe(lattice) (see example below). I only managed to overlap two persp3d plots. My final idea would be to animate both surfaces using play3d(rgl). Thanks in advance for any help. Best, Carlo Giovanni

Dear R-users, I am working with some grid-search optimization for 13 values of an object function. At glance one may compute the object function for each possible combination of set of parameters, but in my case would not be feasible: taking for example 13 possible values for each parameters like, in logarithm scale, 10^seq(-3,3,.5) will lead to 13^13 combinations of results. As a second trial

Dear R-users, I'm struggling in R in order to "squeeze" a matrix without using a for-loop. Although my case is a bit more complex, the following example should help you to understand what I would like to do, but without the slow for-loop. Thanks in advance, Carlo Giovanni Camarda A <- matrix(1:54, ncol=6) # my original matrix A.new <- matrix(nrow=3, ncol=6) # a new

Dear R-users, I would like to know whether there is a way to extract a diagonal of an inverse matrix without computing the inverse of the matrix itself. The size of my matrices are really huge and, also using sparse matrix, computing the inverse leads to storage problems and low speed. In other words, given a square matrix A, I aim to know diag(B), where B=solve(A), without computing solve(A).

Dear R-user, I would like to apply spatial statistics on some historical data, in particular from 1850 to 1900 by registration district of England and Wales. I have searched in the R-archive, but unsuccessfully. Do you know whether R contains those shape files? Or where would be possible to download and use in R? Thanks in advance, Carlo Giovanni Camarda +++++ This mail has been sent through the

Dear R-users, would it be a better way to construct the matrix below without using any for-loop or model.matrix? preferably with some matrix algebra? Thanks in advance, Carlo Giovanni Camarda ## dimensions m <- 3 n <- 4 mn <- m*n k <- m+n-1 ## with a for-loop X <- matrix(0, mn, k) for(i in 1:n){ wr <- 1:m+(i-1)*m wc <- rev(1:m+(i-1)) where <- cbind(wr,wc)

Dear R-users, I would a small problem saving a graph with postscript after using xyplot. Whereas in the R-screen the two lines are solid, once the image is saved as .eps file the second lines (blue in the following example) is dotted. Here there is a simple example. Thanks in advance for your help, Carlo Giovanni Camarda # creating data a1 <- sort(runif(10)) a2 <- sort(runif(10)) a3 <-

I may be doing this wrong! but I have a function which I have simplified a lot below. I want to pass some 'field names' of a data-frame to the function for it to then do some manipulation of. Here's my code: #build a simple dataset mydataset = data.frame (

Dear R-users, I would like to ask whether it's possible (for sure it would be), to plot each rows (or columns) in different graphs and in the same figure region without using the function "par" and then struggling around with "axes" and labels etc. Luckily, I would always have "rows + columns = even number" and the same "ylim". The next one could be a

Dear R-users, I am searching to the "best" way to compute a series of n matrix multiplications between each matrix (mXm) in an array (mXmXn), and each column of a matrix (mXn). Please find below an example with four possible solutions. The first is a simple for-loop which one might avoid; the second solution employs the tensor product but then manually selects the right outcomes. The

Hi, I am performing a two-way ANOVA (2 factors with 4 and 5 levels, respectively). If I'm interpreting the output of summary correctly, then the interaction between both factors is significant: ,---- | ## Two-way ANOVA with possible interaction: | > model1 <- aov(log(y) ~ xForce*xVel, data=mydataset) | | > summary(model1) | Df Sum Sq Mean Sq F value Pr(>F) |

Dear R-Users, without going into details I tried to prepare a simple example to show you where I would need help. In particular I prepare two examples-template for a study I'm conduction on discrete-time methods for survival analysis. Each of this example has two datasets which are basically equal, with the exception that in the former one has individual data and in the latter one aggregated

Dear R-users, I couldn't find a function or some help in R-project web about the Generalized Singular Value Decomposition. In MatLab there is a simple function for this algebric issue (gsvd). Is there anything like that in R? And, if not, could you help me to apply this method in R? Thanks in advance, Giancarlo +++++ This mail has been sent through the MPI for Demographic Rese...{{dropped}}

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Hi list, I am using the capscale function in vegan_2.0-7 to do a constrained principal coordinates analysis, and I kept getting the following error message: Error in Y.r[, oo, drop = FALSE] : subscript out of bounds I googled but I couldn't find an answer. Could anyone tell me why this error msg and what to do? Here is the command I used:

Dear R-users, I would like to show you a simple example that gives an overview of one of my current issue. Although my working setting implies a different parametric model (which cannot be framed in the glm), I guess that what I'll get from the following example it would help for the next steps. Anyway here it is. Firstly I simulated from a series of exposures, a series of deaths (given a

Dear members of this list, I'd like to count missing values using the aggregate function. Something like this: count_nas <- function(arg1) { return(sum(is.na(arg1))) } aggregate(cbind(var1, var2, var3) ~ subject + time, data = mydataset, count_nas) It's not working: I end up with a matrix containing zeros, although there are missings in the data frame. I'd highly

Dear R users, I was wondering how I can replace the values of a vector with the values from in another vector in the same row For example, how can I replace the value of x below with NA when the value of Z in the same row is NA? x <-1:20 z<- c(11, 15, 17, 2, 18, 6, 7, NA, 12, 10,21, 25, 27, 12, 28, 16,17, NA, 12, 10) Many thanks Mintewab ________________________________________ Fr?n: