similar to: Constrainted Nonlinear Optimization - lack of convergence

Dear Helper, I used "constrOptim.nl" and got the value of par. The estimations looks good even if the number of iterations is only 16. But the values of hessian and convergence are both "NULL". I tested the objective function and gradient function by "optim" and didn't see any problem there. With these functions, "optim" gives the convergence value

Hello, This is my first post to the help request list, so I'm going to err on the side of giving too much information. I'm working on writing a simulation in which agents will make repeated production and exchange decisions with randomly chosen partners. The idea is, all agents can produce two goods which they want to consume, they choose a value t in [0,10] which sets their production

Dear List, I'm trying to solve this simple optimization problem in R. The parameters are the exponents to the matrix mm. The constraints specify that each row of the parameter matrix should sum to 1 and their product to 0. I don't understand why the constraints are not satisfied at the solution. I must be misinterpreting how to specify the constrains somehow. library(alabama) ff <-

Hi, I am testing code that is working successfully using constrOptim. I am replacing constrOptim with other solvers to compare benefits and performance. My belief was that, like constrOptim, auglag in the alabama package would eliminate beta vectors that failed the constraints prior to calling the objective function. These betas are not only not in the solution space but also cause

Hi, Use the `auglag' function in "alabama" if you want to get the Hessian at convergence. This typically tends to perform better than `constrOptim.nl'. Also, `constrOptim.nl' does not compute the Hessian. You should not specify method="L-BFGS-B". The default method "BFGS" is better in this setting. Hope this helps, Ravi

Dear List, I have the code below, where I am using the constrained optimisation package, 'constrOptim.nl' to find the values of two values, b0 and b1. I have no problems when I enter further variable information DIRECTLY into the functions, fn, and heq. In this instance I require fn to have -0.0075 appended to it, and in the case of heq, h[1] has -0.2. library(alabama)

Dear R-users, I'm estimating a two- dimensional state-space model using the FKF package. The resulting log likelihood function is maximized using auglag from the Alabama package. The procedure works well for a subset of my data, but if I try to use the entire data set I get the following error message. Error in eigen(a$hessian) : infinite or missing values in 'x' What's even

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Hello dovecot, First poster here. What I want : give a.chaouche at algerian-radio.dz list and read permissions on a.chaouche at backup.algerian-radio.dz. Let's just discuss sharing the inbox then I can do the same for subfolders, in any. a.chaouche at algerian-radio.dz and a.chaouche at backup.algerian-radio.dz are two different users. Details about the domains aren't relevant here I

Make sure to normalize the z coordinates as well as the x/y ones when there are mipmaps present. Fixes 3d mipmap generation, which now uses the blit path. Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> Cc: "10.2" <mesa-stable at lists.freedesktop.org> --- Did a full piglit run on nva8 and nve7 without regressions. The cubemap array mipmap generation test still fails,

This is what I would like to do and it works just fine. Is there a way to shorten this code so I don't have to subset a subset of a subset? d<-subset(subset(subset(subset(x, River.Mile<=202), River.Mile>3), Lagrangian=="Yes"), EventType=="Regular") Stephen -- Let's not spend our time and resources thinking about things that are so little or so large that

ioemu: fix SDL mouse events processing - GetRelativeMouseState always returns the last position, so when the polling loop gets several mouse events in one go, we would send useless ''no move'' events. - So as to make sure we don''t miss any mouse click / double click, we should not use GetRelativeMouseState() to get the button state, but keep records of the button

Hello R users, Can anyone recommend me any package that can be used to solve linear programming subject to nonlinear equality/inequality constraints. Rdonlp2 is now unavailable due to licensing issue. Thanks, Xiaoxi [[alternative HTML version deleted]]

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

A bioligist colleague sent me the following data. x Y 3 1 7 5 14 8 24 0 (Yes, only four data points.) I don't know much about the application, but apparently there are good empirical reasons to use a quadratic model. The goal is to find the X value which maximizes the response Y, and to find a confidence interval for this X value. Finding the maximizing X value is pretty

Hi all, My problem is as follows: I want to run a loop which calculates two values and stores them in vectors r and rv, respectively. They're calculated from some vector x with length a multiple of 7. x <- c(1:2058) I need to difference the values but it would be incorrect to difference it all in x, it has to be broken up first. I've tried the following: r <- c(1:294)*0 rv

>>>>> Joshua Ulrich <josh.m.ulrich at gmail.com> >>>>> on Tue, 6 Dec 2016 09:51:16 -0600 writes: > On Tue, Dec 6, 2016 at 6:37 AM, <frederik at ofb.net> wrote: >> Hi all, >> >> I ran into a segfault while playing with dates. >> >> $ R --no-init-file >> ... >> >

Sorry to all that are angry about the form of my previous mail. I didn't realise what would happen :((. Here it is in (hopefully) plain text (if my mailer doesn't spoil it again): ############## Dear developers, I have a problem with some discrepancy between R 1.2.1 for Windows and R 1.2.2 (and less) for Linux. While trying to correct the wilcox.test (see my previous bug report) I

Suppose I have a 4-D array X with dimensions (dx, dy, dz, dp). I want to collapse the first 3 dimensions of X to make a 2-D array Y with dimensions (dx*dy*dz, dp). Instead of awkward looping, what is a good way to do this? Is there a similar function like reshape in Matlab? Thanks, Gang

Hi everybody, please, could you give me help ? I scanned the help archives and didn't found hints... I want to solve a large sparse linear system subjected to an inequality constrains (all solutions positive) and an equality constrain (all solutions sum to 1), thus I tried to fool constrOptim using: x[1] + 0 + ... + 0 >= 0 ... 0 + 0 + ... + x[n] >= 0 x[1] + x[2] + ... +