search for: lagrangian

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 all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problem...

Dear All, I couple of weeks ago, I’ve asked for a package recommendation for nonlinear optimization. In my problem I have a fairly complicated non-linear objective function subject to one non-linear equality constrain. I’ve been suggested to use the *Rdonlp2* package, but I did not get any results after running the program for 5 hrs. Is it normal to run this type of programs for hours? Also,

..., all other z constraints are z=0, and the Z - sum(z) > 0 inequality constraint. I used default settings, except for attempts to utilize various 'methods', e.g. BFGS, Nelder-Mead. Review of the alamaba package source code leads me to believe that this code automatically generates the Lagrangian of the cost function augmented with Lagrangian multipliers, and also generates the gradient of the augmented Lagrangian. Hence, I assume (perhaps incorrectly), that auglag is automatically generating the dual problem, and attempts to find a solution to the dual problem by calling 'optim'....

...ntercept) lcavol lweight age lbph svi 1.0435803 0.4740831 0.1953156 0.0000000 0.0000000 0.3758199 lcp gleason pgg45 0.0000000 0.0000000 0.0000000 The relative L1 bound was : 0.44 The absolute L1 bound was : 0.8113534 The Lagrangian for the bound is: 17.89198 And the sum of the absolute values of the coefficients are larger than the bound!! Why? Second, the manual says that if I set sweep.out to NULL, the constant term (which is the intercept, right?) will be included in the bound, but when I do so, I get an error "Mat...

Hi All, I'm trying to do the following constrained optimization example. Maximize x1*(1-x1) + x2*(1-x2) + x3*(1-x3) s.t. x1 + x2 + x3 = 1 x1 >= 0 and x1 <= 1 x2 >= 0 and x2 <= 1 x3 >= 0 and x3 <= 1 which are the constraints. I'm expecting the answer x1=x2=x3 = 1/3. I tried the "constrOptim" function in R and I'm running into some issues. I first start off

Dear experts, I'm attempting to solve a constrained optimization problem using the Rdonlp2 package. I created a Lagrange function (L=f(x)-lambda(g(x)-c)), where x is a vector of 16 parameters. This is what I'm using as objective function in the code below. In addition, I set bounds on these parameters (par.u and par.l). When I run the code, I get the error message shown below. Any idea

Dear list, The task view on optimization does not reference a package for non linear constrained optimization problems. Stefan Theussl told me to look at the Rsolnp package, but unfortunately it is not very clear what method is R ported. (The authors ported the matlab code of Yinyu Ye http://www.stanford.edu/~yyye/ <http://www.stanford.edu/%7Eyyye/>) Currently I'm looking for an

i want to estimate parameters with maximum likelihood method with contraints (contant numbers). for example sum(Ai)=0 and sum(Bi)=0 i have done it without the constraints but i realised that i have to use the contraints. Without constraints(just a part-not complete): skellamreg_LL=function(parameters,z,design) { n=length(z); mu=parameters[1]; H=parameters[2]; Apar=parameters[3:10];

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

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] + ... +

...y = binomial(), bound = 21) Coefficients: (Intercept) a b c d e -4.749816 2.776215 4.342661 8.956583 8.661593 1.264660 Family: Family: binomial Link function: logit The absolute L1 bound was : 21 The Lagrangian for the bound is : 1.843283 Thanks -- View this message in context: http://www.nabble.com/Cross-validation-for-logistic-regression-with-lasso2-tf3777173.html#a10680591 Sent from the R help mailing list archive at Nabble.com.

...; > Hi all, > > I need some help about how to calculate w in a SVR in package e1071. > > I have a regression y_i=f(x_i)+e > > where f(*x*)=(w,phi(x))+b > > then go on with the SVR calculation I know that w*=Sum_i=1^n [(á_i - > á*_i)K(x,x_i) ] where á_i and á*_i are the lagrangian multipliers of the > dual form. > > o.k but how I will get it in R? > > When I run my model I have information about the model but I don't know how > to use it to get w. Where are the alphas? Is w a vector or a value? > > Someone can help me please. > > Regards, &g...

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Dear All I am dealing at the moment with optimization problems with nonlinear constraints. Regenoud is quite apt to solve that kind of problems, but the precision of the optimal values for the parameters is sometimes far from what I need. Optim seems to be more precise, but it can only accept box-constrained optimization problems. I read in the list archives that optim can also be used with

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Greetings, R-Wizards: I'm trying to find an extremum subject to a nonlinear constraint. (Yes, I have perused the archives but have found nothing positive.) The details of the problem are these: In a paper published some years ago in Technometrics, ("Confidence bands for cumulative distribution functions of continuous random variables" Technometrics, 25, 77-86. 1983), Cheng and

CRAN (and crantastic) updates this week New packages ------------ * allan (1.0) Alan Lee http://crantastic.org/packages/allan Automates Large Linear Analysis Model Fitting * andrews (1.0) Jaroslav Myslivec http://crantastic.org/packages/andrews Andrews curves for visualization of multidimensional data * anesrake (0.3) Josh Pasek http://crantastic.org/packages/anesrake This

Hi all, A server with [GatewayPorts "yes"] also ignores client's remote bind_address parameter, contrary to what is implied by the current description. Cheers! Index: src/usr.bin/ssh/ssh.1 =================================================================== RCS file: /cvs/src/usr.bin/ssh/ssh.1,v retrieving revision 1.316 diff -u src/usr.bin/ssh/ssh.1 --- src/usr.bin/ssh/ssh.1 18