similar to: optimize simultaneously two binomials inequalities using nlm

Dear R users, I?m trying to optimize simultaneously two binomials inequalities (used in acceptance sampling) which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

Dear R users, I?m trying to optimize simultaneously two binomials inequalities used to acceptance sampling, which are nonlinear solution, so there is no simple direct solution. The 'n' represents the sample size and the 'c' an acceptance number or maximum number of defects (nonconforming) in sample size. The objective is to obtain the smallest value of 'n' (sample size)

I have an advanced question about bootstrapping. There are two datasets. In each bootstrap iteration, I would like to sample One observation per cluster from the first dataset. N observations with replacement from the second dataset. Right now I am using dplyr::sample_n() for first dataset, with this sampling embedded in the program that boot() from the boot package is running to sample the

I don?t know if the last message was with content. So, I sent again. I have installed a Digium card TE210P and unicall for use MFC/R2. I think that it?s all right but I can?t make and receive calls. I?m using asterisk 2.1 with the patch made by Jos? P. Leit?o and the follow libs: libsupertone-0.0.2 libunicall-0.0.3 libmfcr2-0.0.3 zaptel 2.1 My number is 34318300. The Telco send me only 8300.

Hello, I am looking for a package implementing unconditional tests for comparing two binomials (Barnard's test or derivatives). As I am looking for rare genotypes within my groups, my number of subjects in one of the cells of the 2x2 table is often 2-4 resulting in a too conservative result by Fisher's exact test due to the discrete sample space of the test statistic. As I want to use

I have to estimate the following model for several group of observations : y(1-y) = p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y) with constraints : p[1]+p[3] >= 1 p[1]+p[2]+p[3]+1 >= 0 p[3] >= 0 I use the following code : func <- sum((y(1-y) - p[1]*(x^2-y) + p[2]*y*(x-1) + p[3]*(x-y))^2) estim <- optim( c(1,0,0),func, method="L-BFGS-B" , lower=c(1-p[3], -p[1]-p[3]-1,

Hi, I need to solve an optimization problem in R having linear objective function and quadratic constraints(number of variables is around 80). What are the possible choices to do this in R. optim() function only allows box constrained problems. Is it possible in nlm()? Or please tell me if there is any other routine. Thanks Amit

I'm getting a segfault when I call `SDL_Init( SDL_INIT_VIDEO )` within the MCJIT.  If I compile the same program to an EXE I don't have a problem. Are there any general restrictions, or known issues, with loading a library like SDL2 via the MCJIT?  (LLVM-3.8 still) The stack trace, from GDB, is below. I noticed the error actually happens deep inside a transitively loaded GL drive module,

Hi, I have a shared library that makes use of LLVM/clang to add JIT capabilities to a front-end interface in Lua. This shared library is used within an executable application. This all works and builds fine on OSX, but I'm having trouble replicating it for Linux. The build process goes fine, with no changes to the library code, however I'm receiving a SIGABRT caused by an

I am having a strange problem with an asterisk servier using R2 Unicall in Mexico. Most calls go through fine but some of them give me an error like this: -- Executing Dial("SIP/86-db41", "Unicall/g2/014448343600") in new stack -- Called g2/014448343600 Feb 9 21:44:39 WARNING[23069]: chan_unicall.c:2644 handle_uc_event: Unicall/2 event Dialing Feb 9 21:44:45

Lang - I've made some progress writing my register allocator, but now I'm stuck. I have 2 questions for you: 1. I tried running the PBQP allocator (as a dynamic pass), but that didn't work. When I type this: llc -f -load Debug/lib/regalloc.so -regalloc=pbqp simple.bc I get the following error: llc:

Hello! I'm using Asterisk for our office telephony, but we have some problems that still we can't resolve about it. Here they are: 1) merge in/out call recording files I also tried to use a script I found on the internet, called 2wav2mp3 In extensions.conf I added the following lines ; script to be executed when monitoring has been finished MONITOR_EXEC=/usr/local/bin/2wav2mp3 exten

Dear All, Which package/function could i use to solve following linear least square problem? A over determined system of linear equations is given. The nnls-function may would be a possibility BUT: The solving is constrained with a inequality that all unknowns are >= 0 and a equality that the sum of all unknowns is 1 The influence of the equations according to the solving process is

Hello, I'm fairly new to R and I can't work out how to produce a double inequality like (LaTeX) $0 \leq x \leq 1$ in the legend of a graph. If I try > legend(50, 0.1, legend = c(expression(0 <= x <= 1), c(2 <= x <= 3)), pch = c(1,1), col = c(2, 3)) then I get an error message "unexpected '<=' in ...". I've checked the help files for plotmath and

I have a relatively simple finance application of GMM. Given the moment condition: E[m*R]=0 where m=m[theta] I would like to constrain m>0. Any ideas? [[alternative HTML version deleted]]

Hello, we want to identify breakpoints (different phases) in environmental data, algae cell counts of three years with intervals between 7 and 30 days (N=40). We found that breakpoints(cells ~1) works great and identifies 5 very good breaks, however we are uncertain about these, because the data are unequally spaced. Is there a way to include the information about the measurement intervals,

Dear R Users, I would like to make a lesast squares regression similar to that what is done by the command "lm". But additionally, I would like to impose some restrictions: 1) The sum of all regression coefficients should be equal to 1. 2) Each coefficient should assume a value between 0 and 1. (inequality restrictions) Which command is the best to use in order to solve this problem

Dear everybody! take a<-c(5,3,NA,6). if(a[1]!=NA){b<-7} if(a[3]!=5){b<-7} if(a[3]!=NA){b<-7} if(a[3]==NA){b<-7} will alltogeather return Fehler in if (a[1] != NA) { : Fehlender Wert, wo TRUE/FALSE n?tig ist (or simularly). Somehow this is logical. But how else should I get out, whether a certain vector-component has an existing value? Thank you in advance! Yours, Mag. Ferri

I have a spatial salinity field s and a model g(s) ~ Xb where the X comes from slightly modified GAM basis functions. I am trying to deal with the following set of requirements: 1. The underlying physics are linear, and plain salinity (the identity link) is the correct response to my covariates. 2. Dispersion (variance or sd) is almost certainly proportional to the mean. 3. The data s(x,y)

Dear guRus, I am doing a logistic regression using restricted cubic splines via rcs(). However, the fitted probabilities should be nondecreasing with increasing predictor. Example: predictor <- seq(1,20) y <- c(rep(0,9),rep(1,10),0) model <- glm(y~rcs(predictor,n.knots=3),family="binomial") print(1/(1+exp(-predict(model)))) The last expression should be a nondecreasing