search for: nmk

...olks. I have a factor with the following levels in a very large data set: > levels(all$Classical.Statistic) [1] "" "AB;ABD" "CollapsedSteps" "CR_P" "CR_Prop;CR_P;AB" [6] "NMK" "NMK;P" "NMK;P;ABD" "P" "ABD" [11] "CR_P;CollapsedSteps" "NMK;AB;ABD" "NMK;ABD" "NMK;P;AB"...

...on solvers to this noisy and smoothed noise functions we get for instance the following results: (Starting point is always `rep(0.1, 5)`, maximal number of iterations 5000, relative tolerance 1e-12, and the optimization is successful if the function value at the minimum is below 1e-06.) k nmk anms neldermead ucminf optim_BFGS --------------------------------------------------- 1 0.21 0.32 0.13 0.00 0.00 3 0.52 0.63 0.50 0.00 0.00 10 0.81 0.91 0.87 0.00 0.00 Solvers: nmk = dfoptim:...

...going to assume that Kunden is a data frame, and it has columns > (variables) with names like > Umstatz_2011 > and that you want to create new columns with names like > Kunde_real_2011 > > If that is so, then try this (not tested): > > for (year in 2011:2015) { > nmK <- paste0("Kunde_real_", year) > nmU <- paste0("Umsatz_", year) > cat('Creating',nmK,'from',nmU,'\n') > Kunden[[ nmK ]] <- ifelse( Kunden[[ nmU ]] <= 0, 1, 2) > Kunden[[ nmK ]] <- factor( Kunden[[ nmK ]], > lev...

Hi all, I would like to use a loop for tasks that occurs repeatedly: # Groups # Umsatz <= 0: 1 (NICHT kaufend) # Umsatz > 0: 2 (kaufend) for (year in c("2011", "2012", "2013", "2014", "2015")) { paste0("Kunden$Kunde_real_", year) <- (paste0("Kunden$Umsatz_", year) <= 0) * 1 +

...hat I was using in 1975. It still works well as a first-try method for optimization, but generally is less efficient than gradient based methods, in particular because it does not have a good way to know it is finished. As a derivative-free method, it is "not too bad", particularly in the nmk version in the dfoptim package. Indeed, I wish this version were put in optim() as the default, since it can deal with bounds constraints, though slightly less generally and less well than bobyqa or some other methods, and there are a couple of minor details it handles better than N-M in optim() th...

Hi All, I have a situation where I want an 'if' variable to be parameterized. It's entirely possible that the way I'm trying to do this is wrong, especially given the error message I get that indicates I can't do this using an 'if' statement. Essentially, I have data where I think a relationship enters when a variable (here Pwd) is below some value (z). I don't

Hello, I am attempting to use optim under the default Nelder-Mead algorithm for model fitting, minimizing a Chi^2 statistic whose value is determined by a .C call to an external shared library compiled from C & C++ code. My problem has been that the R session will immediately crash upon starting the simplex run, without it taking a single step. This is strange, as the .C call itself works,

Hi, I've got a matrix, Z, of values representing (as it happens) optical power at each pixel location. Since I know in advance I've got a single, convex peak, I would like to do a 2D parabolic fit of the form Z = poly((x+y),2) where x and y are the x,y coordinates of each pixel (or equivalently, the row, column numbers). Is there an R function that lets me easily implement that?

Hello, I am new to R and I am trying to estimate a discrete model with three choices. I am stuck at a point and cannot find a solution. I have probability functions for occurrence of these choices, and then I build the likelihood functions associated to these choices and finally I build the general log-likelihood function. There are four parameters in the model, three of them are associated to

...BtuYWBVPOxG3iJSMM1rBaJPmftYyU6KvTEu4naKbNVJPYcmHYo9eS3I KeQMoCjYn1WZayHqPNGXFVWyrVfAQ0aKDTYs6hVJ6m4kbpBrEMLlygZKFQU2 6iV1xj4sEsaYJXIhaT2mKdVJG9E0ze9hA5X+kFyY8h4R+pF4Tebmnybq8seT Dk0OAjQK0xZOFuiXqCXigSvd3FcjkjIt5DadHJWatX33mIPg4nV4Kt3yxa5k tESoOvNHMVWIFjAM9E7h0QBChvPiJFb0QckLapuDXJ+8j0Brr1XKSdjUn90G nmK86Nfz9BUC4QwVGYG+xTxOKiGRMBXuNXQc08elGVewluJmtqaC1l2+NVBg 4k1eAYSlA0TIaixKocUqdqosCYJolC/Da1Hd2KoddtjzIRphLckJpgUxmj1p OadO8PKebGJ5YjRu02ZNeno0dtNuTVJSNF7TVn5KuPXvk9kWBt09VTLJPCF+ GrilS7UrfjimeH4Y9pi1UuOfTxwW6vOg3T+5Xzl19JuPqqbhkjMC+PjKsjY/ 9t2phY2cQNpfJq0RAFVXVtmldSdTAF2SYhxfmTWbAJuYGeN+a/NvoaCsCmn...