similar to: Vorticity and Divergence

Dear All, A friend of mine seeks help in converting the attached ascii to netcdf. Any assistance will be sincerely appreciated. Regards, Marshall -------------- next part -------------- An embedded message was scrubbed... From: Sepo Hachigonta <shachigo at csag.uct.ac.za> Subject: asscii2netcdf Date: Fri, 05 Sep 2008 19:15:49 +0200 Size: 1292765 URL:

Dear CSAG R users, I will be glad if someone can point out what I am doing wrong or not doing at all in this. I am trying to write out netcdf file in R. I have 26 time step but only the first time step is written. For example: >library(ncdf) >path <- '/home/work/' >forecast <- open.ncdf(paste(path,'cam.1980.2005.nc',sep="")) > fore <-

Dear CSAG R users, I will be glad if someone can point out what I am doing wrong or not doing at all in this. I am trying to write out netcdf file in R. I have 26 time step but only the first time step is written. For example: >library(ncdf) >path <- '/home/work/' >forecast <- open.ncdf(paste(path,'cam.1980.2005.nc',sep="")) > fore <-

Hi, I have been trying to get my asterisk box to send SMS's to my Panasonic dect phone via a Linksys pap2. I believe I have the message centers setup correctly between * and the phone. The pap2 is configured to only use G711a. The Asterisk version is 1.0.7. In my /etc/asterisk/extensions.conf I have [smsphone] exten = 199,1,Goto(smsmorx,${CALLERIDNUM},1) [smsmorx] exten =

Hello R-help, I need to compute matrices of first derivatives of a covariance matrix C with entries given by c_ij=theta*exp(-0.5* sum(eta*(x[i,]-x[j,])^2)), wrt to elements of eta, a m-dimensional vector of parameters, given a n*m data matrix x. So far, I have been computing matrices for each parameter (given by par[index]) analytically, using the following kmatder<- function(x, par, index) {

Hey, R Users my windows is 64 bit windows 7.?I am trying to install the package ucminf into my 64 bit version R but cannot.??the package I downloaded is from http://cran.r-project.org/web/packages/ucminf/index.html?and I installed it with the "install from local zip files", due to I did not connect my computer to internet. did anyone meet this problem and is there a version of

Hi, I've been trying to use optim to minimise least squares for a function, and then get a guess at the error using the hessian matrix (calculated from numDeriv::hessian, which I read in some other r-help post was meant to be more accurate than the hessian given in optim). To get the standard error estimates, I'm calculating sqrt(diag(solve(x))), hope that's correct. I've found

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,

Does anybody know of a function that implements the derivative (gradient) of the multivariate normal density with respect to the *parameters*? It?s easy enough to implement myself, but I?d like to avoid reinventing the wheel (with some bugs) if possible. Here?s a simple example of the result I?d like, using numerical differentiation: library(mvtnorm) library(numDeriv) f=function(pars, xx, yy)

I'm trying to obtain numerical derivative of a probability computed with mvtnorm with respect to its parameters using grad() and jacobian() from NumDeriv. To simplify the matter, here is an example: PP1 <- function(p){ thetac <- p thetae <- 0.323340333 thetab <- -0.280970036 thetao <- 0.770768082 ssigma <- diag(4) ssigma[1,2] <- 0.229502120

Dear all R users, Is there any way to calculate hessian matrix of a given function at any given point? Regards [[alternative HTML version deleted]]

Dear R users When I use OPTIM with BFGS, I've got a significant result without an error message. However, when I use OPTIMX with BFGS( or spg), I've got the following an error message. ---------------------------------------------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS", >

Hi, my name is Marcel R. Lopes. My problem is, I made a code to calculate the estimates of a Cox model with random effects. Used to optimize the R command for this. The estimates were calculated correctly, but the Hessian matrix does not have good values. The same thing was done in SAS and gave good results for the Hessian Matrix. Where is the problem in R? As the Hessian is calculated?. How

Hi, The R CMD check is successful in R 3.0.1 but fails to install package lmerTest under R-devel r63910, Here is what I get: ** preparing package for lazy loading Error in reconcilePropertiesAndPrototype(name, slots, prototype, superClasses, : no definition was found for superclass "merMod" in the specification of class "merModLmerTest" In DESCRIPTION file I have:

Hi, Could anyone tell me what is the command used in R to do 1. Differentiation 2. Newton Raphson method (Numerical Analysis in general...) Are there any packages separately for this? Thanks for your help! BR, Shubha [[alternative HTML version deleted]]

Hello In matlab we have " gradient(F,h) " where h is a scalar uses h as the spacing between points in each direction. Now I need to use this function in R. and I dont know how can I should define my function that I haave "h" in R? thanks [[alternative HTML version deleted]]

Las dos Enviado desde mi iPhone > El 28/11/2013, a las 18:07, "Carlos J. Gil Bellosta " <cgb en datanalytics.com> escribió: > > ¿Numérica o simbólicamente? > > Un saludo, > > Carlos J. Gil Bellosta > http://www.datanalytics.com > > El día 28 de noviembre de 2013 18:03, jmcontreras <jmcontreras en ugr.es> escribió: >> Hola a todos

Hi All, a colleague wants to calculate the Fisher information matrix for a model he wrote (not in R). He can easily get the neg-log-likelihood and the best fit parameters at the minimum. He can also get negLLs for other parameter values too. Given these data, is there a way in R to calculate the Fisher information matrix? Best, Federico -- Federico C. F. Calboli Department of Epidemiology

Hi R-help! I'm trying to understand how R's nlm function updates its estimate of the Hessian matrix. The Dennis/Schnabel book cited in the references presents a number of different ways to do this, and seems to conclude that the positive-definite secant method (BFGS) works best in practice (p201). However, when I run my code through the optim function with the method as "BFGS",

Dear UseRs, I'm curious about the derivative of n!. We know that Gamma(n+1)=n! So when on takes the derivative of Gamma(n+1) we get Int(ln(x)*exp(-x)*x^n,x=0..Inf). I've tried code like > integrand<-function(x) {log(x)*exp(x)*x^n} > integrate(integrand,lower=0,upper=Inf) It seems that R doesn't like to integrate for any n, and I was wondering if anyone knew a way around