similar to: Help with constrained optimization

Hi R-friends, Attached is the SAS XPORT file that I have imported into R using following code library(foreign) mydata<-read.xport("C:\\ctf.xpt") print(mydata) I am trying to maximize logL in order to find Maximum Likelihood Estimate (MLE) of 5 parameters (alpha1, beta1, alpha2, beta2, p) using NLM function in R as follows. # Defining Log likelihood - In the function it is noted as

Dear R-users, May I seek some suggestions from you. I have a long programme written in R with several 'for' loops inside. I just want to get them out by any elegant way (if there is!) to reduce the computational time of the main programme. For instance, is there any smart way for the following programme that will lessen time?

Dear All, May I seek your suggestion on a simple issue. I want to draw vertical lines at some positions in the following R plot. To be more specific, I wish to draw vertical lines at d=c(5.0,5.5,6) and they should go till p=c(0.12,0.60,0.20) . I haven't found any way out, though made several attempts. Please run the following commands first if you are interested in!

Hello there, I am new to using regression in R. I wanted to solve a simple regression problem where I have 2 equations and 2 unknowns. So lets say - y1 = alpha1*A + beta1*B y2 = alpha2*A + beta2*B y1 <- runif(100000, 0,1) y2 <- runif(100000,0,1) alpha1 <- 0.6 alpha2 <- 0.75 beta1 <- 1-alpha1 beta2 <- 1-apha2 I now want this equation to estimate the values of A and B. Both A

Hello R and BUGS users, I am writing a heirarchical model in R to send to BUGS via R2WinBUGS and I am finding it difficult to get the model to run. I seem to be having two problems. 1) I can't seem to send variables classed as factors (Month), is there a way do this? 2) Checking the Log in WinBUGS I can see that the model is Syntactically correct, but Bugs is not able to recognise the the

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]

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]

http://dovecot.org/releases/2.0/alpha/dovecot-2.0.alpha2.tar.gz http://dovecot.org/releases/2.0/alpha/dovecot-2.0.alpha2.tar.gz.sig Changes since alpha1: - All debug messages are now logged to debug log (debug_log_path setting, defaults to info_log_path). Patch by Pascal Volk. - Added support for SORT=DISPLAY IMAP extension. - Added doveadm who command for listing currently logged in users.

http://dovecot.org/releases/1.1/alpha/dovecot-1.1.alpha2.tar.gz http://dovecot.org/releases/1.1/alpha/dovecot-1.1.alpha2.tar.gz.sig Hopefully the next release can be v1.1.beta1. I'm not aware of any major problems and I think I'm pretty much done with new features (except for dbox). The largest changes since alpha1: * Removed THREAD indexing. It's a bit buggy and I think

I'm trying to use garchFit from fSeries, with Student or Skewed Student conditionnal distribution. Let's say that eps (vector) is my series of daily log-returns: data(EuStockMarkets) eps = diff(log(EuStockMarkets[,"CAC"])) library(fSeries) g = garchFit(series = eps, formula.var = ~garch(2,2), cond.dist = "dstd") s = g at fit$series All the coefficients are ok

Hi, Suppose I have the following vector (data points): > x [1] 36.0 57.3 73.3 92.0 300.4 80.9 19.8 31.4 85.8 44.9 24.6 48.0 [13] 28.0 38.3 85.2 103.6 154.4 128.5 38.3 72.4 122.7 123.1 41.8 21.7 [25] 143.6 120.2 46.6 29.2 44.8 25.0 57.3 96.4 29.4 62.9 66.4 30.0 [37] 24.1 14.8 56.6 102.4 117.5 90.4 37.2 79.6 27.8 17.1 26.6 16.3 [49] 41.4 48.9 24.1

I feel like a complete dolt, as I know this question has been asked by others on a fairly regular basis, but I'm going in circles trying to get the following to work: id.prob<-function (tt) { library(mvtnorm) #============================ Makeham<-function(tt) { a2=0.030386513 a3=0.006688287 b3=0.039047537 t<-tt-20 h.t<-a2+a3*exp(b3*t) S.t<-exp(-a2*t+a3/b3*(1-exp(b3*t)))

There is a thread on this topic already: http://finzi.psych.upenn.edu/Rhelp10/2010-August/250934.html I'm rather mystified by a similar problem and wondering whether I've overlooked something obvious. I'm running with latest versions of R and all packages, and latest version of JAGS running under Windows 7. Here's the problem. I have some source code. It's given below -

Hi, I apologize for this often/old question. I found some hints but couldn't solve the problem so far. I have C functions (incl. the header files) as well as the R wrapper functions which I want to use for faster calculations. These functions are included in a R package. The installation process seems to be ok (no errors). I also can load the package without errors. But when I call the

I have both 1.0 alpha1 and alpha2 installed on my test mail server. SSL/TLS does not work on alpha2. I'm using the same config file for both. No errrors in dovecot.log either. Is there a way to increase debugging info without recompiling?

I am trying to run WinBUGS 1.4 from the Ubuntu 6.10 Linux distribution. I am using the R2WinBUGS packages with the source file listed below. WinBUGS appears to run properly, but I get the following message after WinBUGS starts in WINE. Does anyone know what may be causing this error and what the correction may be? Thanks ERROR MESSAGE: fixme:ole:GetHGlobalFromILockBytes cbSize is 13824

Dear experts! I have a minimization problem with non-linear constraint and Objective function(theta)=lambda*(Constr)^2-f(x,theta). Theta is a vector of parameters. I'd like to stop the optimization after the value of the constraint is less or equal some constant value, say d, and save the last computed value of the function. For this purpose, I thought to define the Objective function like

Hi,   I use fCopulae package to draw different graphs of univariate and bivariate skew t.  But the plots titles overlap.  I tried using cex.main, font.main to adjust the size but they still overlaps.  Here is my code: par(mfrow = c(3, 1)) mu = 0 Omega = 1 alpha1 = 0 alpha2 = 1.5 alpha3 = 2 alpha4 = 0.5 Z1 = matrix(dmvst(x, 1, mu, Omega, alpha1, df = Inf), length(x)) Z2 = matrix(dmvst(x, 1, mu,

Dear all, Can any one tell me how can i perform Orthogonal Polynomial Regression parameter estimation in R? -------------------------------------------- Here is an "Orthogonal Polynomial" Regression problem collected from Draper, Smith(1981), page 269. Note that only value of alpha0 (intercept term) and signs of each estimate match with the result obtained from coef(orth.fit). What

Hi all-- We are planning an intervention study for adolescent alcohol use, and I am planning to use simulations based on a hurdle model (using the hurdle() function in package pscl) for sample size estimation. The simulation code and power code are below -- note that at the moment the "power" code is just returning the coefficients, as something isn't working quite right. The