similar to: Solve system of equations (nleqslv) only returns origin

I have a complex function that I want to maximize (I have multiplied this function by -1 so that it becomes a minimization problem in the code below). This function has two equality constraints. I get the programs to run but the answer isn't correct because, when it does converge, at least one of the constraints is violated. Any suggestions? Code below Violated constraint (an easy check):

Hallo HelpeRs, I try to reconstruct some results from an econometric text book (Heij et al. (2004), pp. 218-20). For the data > x <- structure(list(q1 = c(345, 331, 320, 314, 299, 395, 415, 490, 547, 656, 628, 627), d1 = c(1, 1, 1, 1, 1, 1, 1.05, 1.05, 1.05, 1.15, 1.15, 1.15)), .Names = c("q1", "d1"), row.names = as.integer(c(NA, 12)), class =

Douglas Bates wrote: > > The GLMM function in the lme4 package allows you to specify crossed > random effects within the random argument without the need for the > pdBlocked and pdIdent constructions. Simply ensure that your grouping > factors are defined in such a way that each distinct group has a > different level in the grouping factor (this is usually not a problem

Maybe this will clear up what I was initially thinking. In this diagram all lines on the right of the UPSs are power lines and all lines on the left are serial/usb lines. .---. +--|UPS+-----+--------+--------+---... | | A1| | | | | '---' .---+--. .---+--. .---+--. | |Server| |Server| |Server| | | A1 | | A2 | |

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

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

Just to set things straight: The error message "Error in nleqslv(xstart, fun) : Length of fn result <> length of x!" is issued by the underlying nleqslv C function. <fn> refers to the second argument of function nleqslv which is named fn. It is not issued by R itself. Other have already pointed out how to resolve the error. Berend Hasselman

Dear R-users, I use the "nleqslv" function to get parameter estimates by solving a system of non-linear equations. But I also need standard error for each of estimates. I checked the nleqslv manual but it didn't mention about SE. Is there any way to get the SE for each estimate? Thank you very much. [[alternative HTML version deleted]]

Hello all, I am relatively new to R, but enjoying it very much. I am hoping that someone on this list can help me with an issue I am having. I am having issues with iterations over nleqslv, in that the solver does not appear to clean up memory used in previous iterations. I believe I've isolated the/my issue in a small sample of code: library(nleqslv) cons_ext_test <- function(x){

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

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

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+

Santi, In the second line of your function you have the following: f <- numeric(length(x)) This sets the length of this numeric vector (i.e., "f") to the length of the vector "x". Later, inside the function you assign to values to 4 elements of the vector "f". This assumes that "f" is at least 4 element in length. However, you define

Dear all, I am relatively new to R and have had some difficulty in understanding an error i get when running a code to solve a system of non-linear equations, with four equations and two variables. This is my code: ALPHA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) BETA <- c(-0.0985168033402, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4) GAMMA <- c(0.3940672148378, 0.1, 0.15,

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

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 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

In order to implement a subtle memory access optimisation during post-RA scheduling, I want to be able to determine some properties about the memory access. If I have two registers referring to memory, how can I determine if they are derived from the same base-pointer? Often LLVM will optimise to use intermediate registers holding partial displacements, for example, when a 'struct'

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch [SMTP:r-help-bounces at stat.math.ethz.ch] On Behalf Of ernesto > Sent: Friday, January 13, 2006 9:25 AM > To: Mailing List R > Subject: [R] help with gepRglm::likfit.glsm > > Hi, > > I'm exploring likfit.glsm and I need some help. I have to say that I'm > not an MCMC expert ... >

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