similar to: help with NLOPTR

I'm solving 4 complex equations simultaneously. Code is below. The code returns only zero's for the solution though there should also be a non-zero result. I'm pretty confident that the equations are correct because they are straight from a published paper and I checked them pretty thoroughly. The parameter values I used are from the published paper as well. Any suggestions for how

Dear all, I tried running the following syntax but it keeps running for about 4 hours and then i got the following errors: Error in if (is.na(f0$objective)) { : argument is of length zero In addition: Warning message: In is.na(f0$objective) : is.na() applied to non-(list or vector) of type 'NULL' Here is the syntax itself: library('nloptr') library('pracma') #

Dear R community, I have trouble implementing a nested variance-covariance matrix in the lme function. The model has two fixed effects called End and logpgc, the response variable is the logarithm to base 2 of Intensity ( log2(Intensity) ) and the random effects are called Probe and ProbeNo. The model has the following nesting structure: A Pixel is nested within the ProbeNo,the ProbeNo is

a graph question. Thanks a lot in advance. I made two scatterplots on one graph (sigma vs. delta1, sigma vs. delta2) (20 observations of delta1, delta2 and corresponding sigma) the x-axis is sigma, the y-axis is either delta1 or delta2. I connected both scatterplots. To seperate them, one curves is a line with circles, the other curve is a line with squares on it. I want to make a notation

Hi r-users;   I have this values: eign_val <- c(137.810447,3.538721,2.995161,1.685670) alp    <- 1.6549 ;  lamda <- eign_val lamda_m <- min(lamda)   First I calculated manually: delta0 <- 1 delta1 <- alp*delta0*(4-lamda_m*(1/lamda[1]+1/lamda[2]+1/lamda[3]+1/lamda[4]))  delta1 delta2 <- (alp/2)*(delta1*(delta1/alp) + delta0*((1-lamda_m/lamda[1])^2+

Is there an R implementation of a scheme for automatic smoothing parameter selection with loess, e.g., by minimizing one of the AIC/GCV statistics discussed by Hurvich, Simonoff & Tsai (1998)? Below is a function that calculates the relevant values of AICC, AICC1 and GCV--- I think, because I to guess from the names of the components returned in a loess object. I guess I could use

Hi all, I'm not familiar with R programming and I'm trying to reproduce a result from a paper. Basically, I have a dataset which I would like to model in terms of successive increments, i.e. (y denote empirical values of y) y_1 = y1, y_2 = y1 + delta1, y_3 = y1 + delta1 + delta2. ... y_m = y1 + sum_2^m delta j where delta_j donote successive increments in the y-values, i.e. delta

Dear R developers! Considering I got no response or comments in the general r-help forum so far, perhaps my question is actually better suited for this list? I have added some more hopefully relevant technical details to my original post (edited below). Any comments gratefully received! Best regards, David Kreil. ---------- Dear R experts, I have a problem that is a related to the question

Hi there, I've sent this e-mail to the list twice but didn't get it back from the list. Have it reach list members? cheers, Ronaldo ---------- Forwarded message ---------- From: Ronaldo Prati <rcprati at gmail.com> Date: 14/12/2006 11:59 Subject: Model formula question To: r-help at stat.math.ethz.ch Hi all, I'm not familiar with R programming and I'm trying to

Dear R experts, Attached you can find the expression of a loglikelihood function which I would like to maximize in R. So far, I have done maximization with the combined use of the mathematical programming language AMPL (www.ampl.com) and the solver SNOPT (http://www.sbsi-sol-optimize.com/manuals/SNOPT%20Manual.pdf). With these tools, maximization is carried out in a few seconds. I wonder if that

Dear all, I am a new user to R and I am using pracma and nloptr libraries to minimize a numerical integration subject to a single constraint . The integrand itself is somehow a complicated function of x and y that is computed through several steps. i formulated the integrand in a separate function called f which is a function of x &y. I want to find the optimal value of x such that the

I noticed a problem using R 2.7.1 on Windows XP SP2 with the precompiled Atlas Rblas.dll. Running the code below causes R to crash. I started R using Rgui --vanilla and am using the precompiled Atlas Rblas.dll from cran.fhcrc.org dated 17-Jul-2007 05:04 for Core2 Duo. The code that causes the crash: x <- rnorm(100) y <- rnorm(100) z <- rnorm(100) loess(z ~ x * y) loess(z ~ x) does

Hi, I have a bivariate longitudinal dataset. As an example say, i have the data frame with column names var1 var2 Unit time trt (trt represents the treatment) Now suppose I want to fit a joint model of the form for the *i* th unit var1jk = alpha1 + beta1*timejk + gamma1* trtjk + delta1* timejk:trtjk + error1jk var2 = alpha2 + beta2*timejk + gamma2* trtjk + delta2* timejk:trtjk +

Dear all, The attached code is supposed to minimize a numerical integration subject to a non linear constraint. The code runs for 2 days& more without giving an output. Also, when i change the value of "m<-100" to "m<-1" it gives an output in areasonable period but with a message " maximum number of iterations in romberg has been reached". I need to : 1-

I can't install rugarch package because installation of nloptr package fails . I use opensuse 12.3 # uname -a Linux candide 3.7.10-1.11-desktop #1 SMP PREEMPT Thu May 16 20:27:27 UTC 2013 (adf31bb) x86_64 x86_64 x86_64 GNU/Linux my gcc version is 4.8.1 I compiled and installed R 3.01 . then I tried to install rugarch package but it fails because it can't install depended package nloptr.

Dear: Continuing the issue of 'ifelse'! I selecting the data whose 'x2'=1 for maximizing likelihood. I used two way to do this but the results are different. 1.Way one I use the data for x2=1 and run the program. It works for me. Tthe program is described as below: function (parameters,y1,x11) { p<-parameters[1] alpha1<-parameters[2] beta1<-parameters[3]

Hello, I am running Dovecot 1.0.5 and seem to have lots of errors in my Dovecot logs. The worst errors are things like: Oct 30 16:11:42 delta2 dovecot: IMAP(x): Corrupted transaction log file /home/spamcop-net2/deputies/dovecot.index.log: end_offset (392) > current sync_offset (388) Oct 30 16:11:42 delta2 dovecot: IMAP(x): file mail-index-sync-update.c: line 841

This is an OpenPGP/MIME signed message (RFC 2440 and 3156) --------------enig807B2312A20EAF60129FDDFA Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable Hi, I am writing this email, because I am not sure if the issue I have discovered is a bug or not. For a few days I have been fiddling around with a small program that calculates the reflectance of

Dear All: I tried to fit negative binomial distribution to data in terms of mean and mean is also a quadratic function of another variable. The likelihood function is: function (parameters, y1,x11) { p<-parameters[1] alpha1<-parameters[1] beta1<-parameters[2] delta1<-parameters[3] mu<-alpha1+beta1*(x11)+delta1*(x11^2) ifelse(y1>=0|x11>=0, L<-

Dear: I try to revise the maximum likelihood function below using something constrains. But it seems something wrong with it. Becasue R would not allow me to edit the function like this. It is very appreciate if you can help. function (parameters,y,x1,x2) { p<-parameters[1] alpha1<-parameters[2] beta1<-parameters[3)] delta1<-parameters[4] alpha2<-parameters[5]