similar to: multidimensional integration not over a multidimensionalrectangle

my=function(x){ len=1 for(i in 1:len){ y[i]=x[i] } g=1 w=NULL t=NULL for(i in 1:len)w[i]=x[i+len] for(i in 1:len)t[i]=x[i+2*len] for(i in 1:len)g=g*dnorm(y[i])*dnorm(w[i])*dnorm(z[i]) return(g) } cuhre(6,1,my,rep(-100,6),rep(100,6)) Error in crff(match.call(), integrand, "cuhre", libargs, ...) : Additional argument not expected in the integrand function function change to

Hi there, I am using SAS Proc NLMIXED to maximize a likelihood with multivariate normal random effects. An example is the two part random effects model for repeated measures semi-continous data with a cluster at 0. I use the "model y ~ general(loglike)" statement in Proc NLMIXED, so I can specify a general log likelihood function constructed by SAS programming statements. Then the

Like kile for LaTeX, Linux/KDE's kate editor is an excellent editor for R, with easy code submission to a running R process. Syntax highlighting is good. I have not been able to figure out two things: - how to automatically reformat a line or region of text using good indentation rules (Emacs/ESS make this so easy by just hitting Tab while the cursor is in a line, or highlighting a

Dear all, May I do multiple integration using R? I was looking adapt but it is saying it integrates a scalar function over a multidimensional rectangle. I have integrand of several variable and upper, lower limit too variable. I wanted to see the result using adapt (though it is not for this purpose, I suppose) Func<-function(x){(x[1]*x[2])} adapt(2, lo=c(0,1), up=c(1,x[1]), functn=Func) it

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What is the correct syntax for finding the area under the standard normal density for a particular value of z? Thanks [[alternative HTML version deleted]]

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A student of mine wants to use R to do some nonmetric multidimensional scaling. According to the R FAQ, there's a package called pcurve that computes multidimensional scaling solutions, but I was not able to locate it the contrib page (I am a Windows user with R version 1.4.1). Can anyone tell me whether it is possible to do nonmetric multidimensional scaling with R, and if so, how? John

Hello list. Another 'puzzle' for which I don't have a clean solution. Say I have a multidimensional object, e.g.: Mm<-matrix(1:6, nrow=2, dimnames=list(c("a","b"), c("g","h","i"))) And on the other hand I have a list Ind<-list("b","g") This holds, for each dimension, an indexer for that dimension. Now I would

Hello. I have a 4 dimensional array and I want to fill in the slots with values which are a function of the inputs. Through searching the forums here I found that the function "outer" is helpful for 2x2 matrices but cannot be applied to general multidimensional arrays. Is there anything which can achieve, more efficiently than the following code, the job I want? K <-

Consider the following data frame X <- data.frame(Titanic) Does anyone know of an easy way to convert X into a multidimensional array? Example that doesn't work X <- as.array(X, dim=c(4,2,2,2)) To do what I need, X needs to be converted into an array of dimensions c(4,2,2,2) in this case, not a table. Thanks in advance.

I am moving this to r-devel. The problem and solution below posted on r-help could have been a bit slicker if %*% worked with multidimensional arrays multiplying them so that if the first arg is a multidimensional array it is mulitplied along the last dimension (and first dimension for the second arg). Then one could have written: Tbar <- tarray %*% t(wt) / rep(wti, each = 9) which is a bit

On Aug 2, 2019, at 8:57 AM, Michael Kruse <llvmdev at meinersbur.de> wrote: >> This is why I ask whether its makes sense to add this to LLVM IR: If you want HPC style loop transformations, I don’t think that LLVM IR itself will ever be great, even with this. This might make some narrow set of cases slightly better, but this is far from a solution, and isn’t contiguous with getting to

Dear R list Would anyone be able to tell me whether it is possible to do "enhanced multidimensional scaling" (enhanced MDS) in R? In other words, something that goes beyond "cmdscale" by iteratively improving the fit between observed dissimilarities and inter-object distances, using the KYST algorithm (Kruskal, 1964). I have found several implementations of non-metric MDS

Hi, I am approximation a value function (in dynamic programming) V: R^n->R. In different versions of the problem, n is between 2 and 5. I would like to use splines to use this, I checked the mailing list and CRAN but couldn't find anything that would help me (Tps in fields is too slow, cobs would be really nice but seems to be one-dimensional). Is there any package that would at least

Hi there I know, I'm sure you discussed this stuff 100 times, but I really have a basic understanding problem, if and how do I create a multidimensional array in R. I'm coming from MATLAB and there it's as easy as you ever could imagine. Ok, so, I want to have an array, where I can fill in data from a Excel spreadsheet. The array should be addressed like this:

Hi, I have a multidimensional data-set( multiple 'x' variables with a target variable). I want to take it to a higher dimensional space so that I can apply classification technique with ease . Is there a package in R which would allow me to take these data points from lower dimensional space to higher dimensions? so that is that higher dimension I can apply classification techniques to be

Hi all, is it possible to create a multidemensional list? Haven't found anything in the list() help page. Thanks, Sven -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- 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, I just encountered what I thought was strange behavior in MDS. However, it turned out that the mistake was mine. The lesson learned from my mistake is that one should plot on a square pane when plotting results of an MDS. Not doing so can be very misleading. Follow the example of an equilateral triangle below to see what I mean. I hope this helps others to avoid this kind of headache.

Take a look at package mgcv. Hope this helps. --Matt -----Original Message----- From: RenE J.V. Bertin [mailto:rjvbertin at despammed.com] Sent: Thursday, February 27, 2003 1:39 PM To: r-help at stat.math.ethz.ch Subject: [R] multidimensional function fitting Hello, I have been looking around for how to perform a multidimensional, arbitrary function fit (in any case non-linear; more below),