search for: inequ

Dear R-users, in the last days I have been trying to estimate a normal linear model with equality and inequality constraints. Please find below a simple example of my problem. Of course, one could easily see that, though the constraints are consistent, there is some redundancy in the specific constraints. Nevertheless my actual applications can get much larger and I would not like to manually check fo...

Dear All, I would like to minimise a nonlinear function subject to linear inequality constraints as part of an R program. I have been using the constrOptim function. I have tried all of the methods that come with Optim, but nothing finds the correct solution. If I use the correct solution as the vector of starting values, though, my program does output the correct solution...

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 weighted too. llAx-bll2 * weight with xi >=0 and sum(x)=1 I?m pleased about every suggestion. Thank you and best regards Thomas -- View...

...rs, 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 in a computationally efficient way? Thank you in advance for your help, Harald Bartel -- ------------------------------------------------------ PROZENTOR GmbH Financial Content Provider Bergstr. 67 10115 Berlin...

Hello, I was interested in trying to write an R script to calculate a UCL for a lognormal distribution using the Chebyshev Inequality — MVUE Approach (based on EPA’s guidance found in http://www.epa.gov/oswer/riskassessment/pdf/ucl.pdf). This looks like it should be straight forward, but I am need to calculate an MVUE for the population mean and an MVUE for the population variance, which requires a value (g_n) from a table A...

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...

...") print(1/(1+exp(-predict(model)))) The last expression should be a nondecreasing sequence, as fitted probabilities make no sense to decrease in this case. Is there any elegant way to constrain the model fit? Right now, I am trying to do this by defining a "large" set of linear inequalities and using constrOptim() on the log-likelihood. However, this seems to be very sensitive to the starting values, and I am not really happy with the results. BTW: yes, working with lrm() would probably be more natural, but lrm() breaks down on my data because of a rank-deficient informatio...

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. 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...

...ix/sh ../../depcomp cc -std -DHAVE_CONFIG_H -I. -I. -I../.. -I/usr/pkg/include -ieee -O2 -I/usr/pkg/include - I/usr/pkg/include -c file-cache.c cc: Error: file-cache.c, line 70: In this statement, "cache- >mmap_base" and "(-1)" may not be compared for equality or inequality. if (cache->mmap_base == MAP_FAILED) { --------------------^ cc: Error: file-cache.c, line 79: In this statement, "cache- >mmap_base" and "(-1)" may not be compared for equality or inequality. if (cache->mmap_base == MAP_FAILED)...

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-alph...

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

Hello, I watched your YouTube videos for explanation for R package. They are really helpful for new beginner for using R. Please I need your help for solving inequalities that contain beta functions using R studio. I attached the file that contains this inequalities. I appreciate your help and looking forward to hear from you. Akram -------------- next part -------------- A non-text attachment was scrubbed... Name: Inequalities.pdf Type: application/pdf Siz...

...on problem from Matlab into r. The matlab code is as follow: options = optimset('Diagnostics','on'); [x fval exitflag] = linprog(f,A,b,Aeq,beq,lb,ub,[],options); exitflag fval x=round(x); Where: f = Linear objective function vector (vector of 45,rows) A = Matrix for linear inequality constraints (3colums 45 rows matrix) b = Vector for linear inequality constraints (3 rows vector) Aeq = Matrix for linear equality constraints (45 colums, 8 rows ) beq = Vector for linear equality constraints (8 rows vector) lb =Vector of lower bounds (45 rows) ub = Vector of upper bou...

Hi folks, Pls help me to understand follow; An Introduction to R 2.4 Logical vectors http://cran.r-project.org/doc/manuals/R-intro.html#R-and-statistics 1) > x [1] 1 2 3 4 5 > temp <- x != 1 > temp [1] FALSE TRUE TRUE TRUE TRUE > 2) > x [1] 1 2 3 4 5 > temp <- x > 1 > temp [1] FALSE TRUE TRUE TRUE TRUE Why NOT > temp [1] TRUE FALSE FALSE FALSE

Hi folks, Pls help me to understand follow; An Introduction to R 2.4 Logical vectors http://cran.r-project.org/doc/manuals/R-intro.html#R-and-statistics 1) > x [1] 1 2 3 4 5 > temp <- x != 1 > temp [1] FALSE TRUE TRUE TRUE TRUE > 2) > x [1] 1 2 3 4 5 > temp <- x > 1 > temp [1] FALSE TRUE TRUE TRUE TRUE Why NOT > temp [1] TRUE FALSE FALSE FALSE

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,

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,

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]]

Dear, I am using the solnp command (package Rsolnp) for a problem with equality and inequality constraints. I am not getting convergence for my problem but apart that I get 1 warning per iteration saying: ?In cbind(temp, funv) : number of rows of result is not a multiple of vector length (arg 1)?. I checked for equality and inequality functions and they seem fine to me. Where thi...

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)