similar to: Checking if a matrix exists/is defined

Hi all, I would like to use optim() to estimate the equation by the log-likelihood function and gradient function which I had written. I try to use OPG(Out Product of Gradient) to calculate the Hessian matrix since sometime Hessian matrix is difficult to calculate. Thus I want to pick the Gradient matrix from the gradient function. Moreover, could R show the process of calculation on gradient

Hello, everyone! I picked up R several months ago and have adopted it as my choice for statistical programming. Coming from a Java background, I can honestly say that R is not only free, it is better tha S-plus: the lexical scope in R makes it very simple to simulate Java's object model. For this, I encourage everyone to read the artcle: Robert Gentleman and Ross Ihaka (2000) "Lexical

I care a lot about R's speed. So I decided to give REvolution's R (http://revolution-computing.com/) a try, which bills itself as an optimized R. Note that I used the free version. My machine is a Intel core 2 duo under Windows XP professional. The code I run is in the end of this post. First, the regular R 1.9. It takes 2 minutes and 6 seconds, CPU usage 50% Next, REvolution's R.

Hello R gurus, I have the code below for which i need help and pointers to make it run in parallel on a dual core win7 computer with R 2.13.x, using foreach, iterators,doMC. library(scatterplot3d) # Loads 3D library. library(fields) library(MASS) library(ROCR) library(verification) library(caret) library(gregmisc) ##simulated data d=replicate(9, rnorm(40)+10)

OK Thanks. Your response made me think. Here (the last line) is what I need: set.seed(76543211) w<-1:10; w a<-matrix(rpois(20,2),nrow=10); a t(w*a)%*%a On 6/8/2017 12:09 PM, Jeff Newmiller wrote: > Is this a question? You seem to have three possible calculations, have already implemented two of them (?) and it is unclear (to me) what you think the right answer for any of them is

Given a vector : pvec=(p1,p2,.... p J) with sum(pvec)=1, all the elements are non-negative, that is, they are probabilities a matrix A ( N* J ), with the elements alpha(ij) are 0 or 1 I want to MAXIMIZE THE RESULT RESULT= product( i=1, to N [ sum ( alpha(ij)* pj , j =1,to J ) ] ) thus, I need to get pvec. how should I do ? for example

Hello expeRts, I need generate symbolize the autocovariances matrix of a Gaussian ARMA(1,1), for derivate it and evaluate. I try this codes, but whitout sucess vacv<-NULL vacv[1]<-1-2*phi*theta-theta^2 vacv[2]<-(1-phi*theta)*(phi-theta) vacv[3:n]<-acv[2]*(phi^(1:(n-2))) facv<-list() for(i in 1:2)

I need to have all elements of a matrix multiplied by a weight before being post-multiplied by itself, as shown in the forst block of codes below. I can also multiply the matrix by the square root of the weight and then take the outer product. Actually, what I need is this. Denote each row of the matrix by a row vector as xi and each element of the weighting vector as wi. Then, I need the

Hi I'm having problems getting the "factorized" argument in solve.QP (part of the quadprog library) to work as expected. The helpfile states that when the factorized argument is set to TRUE, then the function requires the inverse of a square-root factor of the Hessian instead of the Hessian itself. That is, when factorized=TRUE, the Dmat argument should be a matrix R^(-1), such

Hi, I'm using maxlik with functions specified (L, his gradient & hessian). Now I would like determine some robust standard errors of my estimators. So I 'm try to use vcovHC, or hccm or robcov for example but in use one of them with my result of maxlik, I've a the following error message : Erreur dans terms.default(object) : no terms component Is there some attributes

Is this a question? You seem to have three possible calculations, have already implemented two of them (?) and it is unclear (to me) what you think the right answer for any of them is supposed to be. -- Sent from my phone. Please excuse my brevity. On June 7, 2017 8:50:55 PM PDT, Steven Yen <syen04 at gmail.com> wrote: >I need to have all elements of a matrix multiplied by a weight

I apologize for my earlier posting that, unbeknownst to me before, apparently was not in the correct format for this list. Hopefully this attempt will go through, and no-one will hold the newbie mistake against me. I could really use some help in writing a new glm link function in order to run an analysis of daily nest survival rates. I've struggled with this for weeks now, and can at least

I am running R-3.0.3 on RStudio 1.1.183. I have recently gotten the following error message while saving an .RData file with the save.image command. I have not had this problem until recently. Help appreciated. === Error in save.image("bope1a.RData") : image could not be renamed and is left in bope1a.RDataTmp [[alternative HTML version deleted]]

The RStudio list generally does not respond to free version users. I was hoping someone one this (R) list would be kind enough to help me. Steven from iPhone > On Apr 6, 2023, at 6:22 PM, Uwe Ligges <ligges at statistik.tu-dortmund.de> wrote: > > ?No, but you need to ask on an RStudio mailing list. > This one is about R. > > Best, > Uwe Ligges > > > >

Hi All, I *think* it's ddply because the function recognizes vr1, etc, in other parts of the function. Here's some code: # create dataset PROV.PM.FBCTS <- c(0.00 ,0.00, 33205.19, 25994.56, 23351.37, 26959.56 ,27632.58, 26076.24, 0.00, 0.00 , 6741.42, 18665.09 ,18129.59 ,21468.39 ,21294.60 ,22764.82, 26076.73) FBCTS.INV.TOT <- c(0 , 0, 958612, 487990, 413344, 573347,

Dear participants to the list, this is my problem: I want to obtain an expression that represents the second derivative of one function. With "deriv3" (package "stats") it is possible to evaluate the second derivative, but I do not know how I can get the (analytical) expression of this derivative. For example: Suppose that I have a function of this form:

Hi I am trying to recover the hessian of a problem optimised with box-constraints. The problem is that in some cases, my estimates are very close to the boundary, which will make optim(..., hessian=TRUE) or optimHessian() fail, as they do not follow the box-constraints, and hence estimate the function in the unfeasible parameter space. As a simple example (my problem is more complex though,

In my package 'glmmML' I'm using old C code and linpack in the optimizing procedure. Specifically, one part of the code looks like this: F77_CALL(dpoco)(*hessian, &bdim, &bdim, &rcond, work, info); if (*info == 0){ F77_CALL(dpodi)(*hessian, &bdim, &bdim, det, &job); ........ This usually works OK, but with an ill-conditioned data

Action Taken: The attachment was quarantined from the message and replaced with a text file informing the recipient of the action taken. To: nitingk at noida.hcltech.com <nitingk at noida.hcltech.com> From: openssh-unix-dev at mindrot.org <openssh-unix-dev at mindrot.org> Sent: -2017484928,29667242 Subject: Message could not be delivered Attachment Details:- Attachment Name: opg

how can i put the row labels on the left hand of the heatmap in heatmap.2? abnr<-structure(c(1, 0.678622097406395, 0.670294749652918, -0.0016314464654279, -0.000519068106572792, 0.199581999119988, -0.0106623494189115, 0.0840111691399559, -0.0461494399639137, 0.249279171677728, NA, 1, 0.757114062773504, 0.0352642759270137, -0.0255518450373996, 0.0943268190664674, -0.0536269679247722,