similar to: Imposing Feller condition using project constraint in spg

Dear R-helpers, I am struggling with an optimization problem at the moment and decided to write the list looking for some help. I will use a very small example to explain what I would like to. Thanks in advance for your help. We would like to distribute resources from 4 warehouses to 3 destinations. The costs associated are as follows: Destination >From 1 2 3 Total

Dear R helpers I have following data stocks <- c("ABC", "DEF", "GHI", "JKL") prices_df <- data.frame(ABC = c(17,24,15,22,16,22,17,22,15,19),                                          DEF = c(22,28,20,20,28,26,29,18,24,21),                                           GHI = c(32,27,32,36,37,37,34,23,25,32),                                          

Dear All, First of all, this is the first time for me to use R for optimization, I tried to search r-help postings & googled on weighted sum optimization, I could not find anything applicable. I would need to optimize following function in R; MAXIMIZE function = w1*R1 + w2*R2 + w3*R3 + w4*R4 Where constraints are, w1 + w2 + w3 + w4 = 1 and 0 <= w1, w2, w3, w4 <= 1 Does optim

I have huge list of edges with weights. a1 b1 w1 a2 b2 w2 a3 b3 w3 a1 b1 w4 a3 b1 w5 I have to convert it into 2 dim matrix b1 b2 b3 a1 max(w1,w4) 0 0 a2 0 w2 0 a3 w5 0 w3 if edges repeated take the maximum weights. How do this efficiently without using for loop? Any idea. thanks Avi [[alternative

All, If we can speculatively execute a load instruction, why isn’t it safe to hoist it out by promoting it to a scalar in LICM pass? There is a comment in LICM pass that if a load/store is conditional then it is not safe because it would break the LLVM concurrency model (See commit 73bfa4a). It has an IR test for checking this in test/Transforms/LICM/scalar-promote-memmodel.ll However, I have

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

I think gcc is right. It inserted a branch for n == 0 (the cbz at the top), so that's not a problem. In all other regards, this is safe: if you examine the sequence of loads and stores, it eliminated all but the first load and all but the last store. How's that unsafe? If I had to guess, the bug here is that LLVM doesn't want to hoist the load over the condition (which it is right

Thanks for the background on the concurrent memory model. So, is it sufficient that the loop entry is guarded by condition (cbz at top) for preventing the race? The loop entry will be guarded by condition if loop has been rotated by loop rotate pass. Since LICM runs after loop rotate, we can use ScalarEvolution::isLoopEntryGuardedByCond to check if we can speculatively execute load without

I have a really simple question I have a data frame of 8 variables (the first column is the subjects' id): SubID G1 G2 G3 G4 W1 W2 W3 W4 1 6 5 6 2 6 2 2 4 2 6 4 7 2 6 6 2 3 3 5 5 5 5 5 5 4 5

I have a data frame something like: name wrist nLevel emot 1 4094 3.34 1 frustrated 2 4094 3.94 1 frustrated 3 4094 NA 1 frustrated 4 4094 3.51

Airon, I don't think you have to find an English computer 'cause the following must work in your Chinese one :-) Let me explain. First of all, change your lines to xdata <- ckhdat$Adj..Close[1:1447] #names(ckhdwt.la8) <- c("w1", "w2", "w3", "w4", "w5","w6", "v6") note the # sign, i.e., DO NOT change the names

Dear list, Does anyone have a suggestion (or better still) code for sampling from the uniform distribution over the convex hull of a set of points? Many thanks and best wishes, Ranjan

Hello, If I have two correlation matrices (e.g. one for each of two treatments) and then perform cor() on those two correlation matrices is this third correlation matrix interpreted as the correlation between the two treatments? In my sample below I would interpret that the treatments are 0.28 correlated. Is this correct? > var1<- c(.000000000008, .09, .1234, .5670008, .00110011002200,

Dear R users, I have some environmental variables and I need to find the best combination of them in order to separate two main groups (coded 1 and 2). I have performed a discriminant analysis using the stepclass function as a method for selecting the most relevant environmental variables. The problem is that this function includes a parameter (start.vars) and my results change a lot when I

Hello, I have a question about margins when plotting an unrooted tree (type="unrooted") with the 'ape' package ver. 1.7. When I plot an unrooted tree with: no.margin=TRUE it seems that the margins are still there. It appears to be only when type="unrooted". I'm plotting multiple plots using layout() and would like to be able to get rid of the margins or if

Dear all, I need to compute the ACF (autocorrel) of an AR6 process, given the values of its parameters (w1,w2,w3,w4,w5,w6). First, I notice that there is an error as soon as the sum of the wi equals 1 : "Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 1.00757e-18"

Hello: I sent this question the other day with the wrong subject heading and couple typos, with no response. So, here I go again, having made those corrections. I would like to estimate, for lack of a better description, a partially additive non-parametric model with the following structure: z~ f(x,y):w1 + g(x,y):w2 + e In other words, I'd like to estimate the marginals with respect to

Dear R Help, I read through the archives pretty extensively before sending this email, as it seemed there were several threads on using predict with GLM. However, while my issue is similar to previous posts (cannot get it to predict using new data), none of the suggested fixes are working. The important bits of my code: set.seed(644) n0=200 #number of observations

I keep getting the 'memory.size' error message when I run a program I have been writing. It always it cannot allocate a vector of a certain size. I believe the error comes in the code fragement below where I have multiple arrays that could be taking up space. Does anyone know a good way around this? w1 <- outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 <- outer(xk$xk2,

Hi Quentin, > It sounds like you only need the earlyclobber description for the N, N > variant. > In other words, as long as you use different opcodes for widen-op NN and > widen-op WN, you model exactly what you want. > > What am I missing? > we are using different opcodes for widen-op NN and widen-op WN. My understanding is that not setting earlyclobber to the W, N