similar to: Trouble with Optimization in "Alabama" Package

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 <-

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)

Hello, I am attempting to utilize the 'alabama' package to solve a constrained nonlinear optimization problem. The problem has both equality and inequality constraints (heq and hin functions are used). All constraints are smooth, i.e. I can differentiate easily to produce heq.jac and hin.jac functions. My initial solution is feasible; I am attempting to maximize a function, phi. As

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, 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

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

Hi all! I played around with the LLVM LTO example(https://llvm.org/docs/LinkTimeOptimization.html#example-of-link-time-optimization), but got some questions. As the document says, the function foo4 should be removed. However, under my test, function foo4 is not removed. I have tried both gnu ld with LLVMgold.so and lld, neither of them removes function foo4. I compile and run the example as

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

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https://bugzilla.netfilter.org/show_bug.cgi?id=842 Summary: Addition of iptables rule referencing an ipset of the wrong address family does not fail Product: ipset Version: unspecified Platform: All OS/Version: All Status: NEW Severity: normal Priority: P5 Component: default

Hi the list In the DESCRIPTION file of my package foo0, I have: Depends: foo1 Imports: foo2 Suggest: foo3 Enhence: foo4 If I understand correctly, to install foo0 on my computer, I need to already have foo1, foo2, foo3. foo4 is not necessary. I my R sesssion, when I will write: library(foo0), then the package foo1 will be attach. foo2, foo3 and foo4 will not. Is that correct? But what is

Full_Name: Ross Boylan Version: 2.2.0 OS: Linux Submission from: (NULL) (65.175.48.58) \eqn{{\bf\beta}_j}{b(j)} in my .Rd file produces this error -------------------------------------------- ! Missing $ inserted. <inserted text> $ l.7 \eqn{{\bf\beta}_j}{\bf\beta}_ jnormal-bracket5bracket-normal{b(j)} -- ! Missing $ inserted. <inserted

Full_Name: Hin-Tak Leung Version: R 2.2.0 OS: x86 linux Submission from: (NULL) (131.111.126.242) Rgnome depends libglade 0.x and libxml 1.x . They are no longer shipped with Redhat EL4. (I know they are still in fedora core 4). Just a wish-list.

Hi All, I compiled the following code on my linux PC using clang with PIE option- struct struct4 {char a; char b; char c; char d; }; struct struct4 foo4 = {'a','2','c','4'}; struct struct4 fun4() { return foo4; } int main() { fun4(); return 0; } > clang -g -fPIE structs.c In GDB session when i call p/c fun4() i get something like below- (gdb) p/c

Using a Polycom 550 and 650 phones on my Asterisk server for testing. I can't figure out why the volume is so low. How can I adjust the volume control on Asterisk? It's at max on the handset phones. Thanks! Hin

# ./imaptest host=127.0.0.1 port=143 user=tstem38 pass=pass4you mbox=/ gpfs/users/t/s/tstem38/IMAP/foo4 Panic: file client.c: line 620: assertion failed: (idx >= array_count(&clients) == NULL) IOT/Abort trap(coredump) -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 2541 bytes Desc: not available

Hi all, I am trying to construct a pairwise coocurrence matrix for certain terms appearing in a number of documents. For example I have the following table with binary values showing the presence or absence of a certain term in a document: term1 term2 term3 term4 term5 doc1 1 1 0 0 1 doc2 1 1 0 1 1 doc3 1 0 0 0 1 And I want to have a matrix with the number of the pairwise coocurrencies. So,

Let's suppose I have userids and associated attributes... columns a and b a <- c(1,1,1,2,2,3,3,3,3) b <- c("a","b","c","a","d","a", "b", "e", "f") so a unique list of a would be id <- unique(a) I want a matrix like this... [,1] [,2] [,3] [1,] 3 1 2 [2,] 1 2 1 [3,]

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

Hi! I wonder if llvm::APFloat::toString() can be const since it should not modify the APFloat. -Jochen